CONVOLUTIONAL NEURAL NETWORKS FOR DETECTION OF MALFORMATIONS OF CORTICAL DEVELOPMENT

Import packages and functions

In [1]:
import matplotlib as mpl
%matplotlib inline
from PIL import Image
import numpy as np
import pandas as pd
import os
from skimage.color import gray2rgb
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from mpl_toolkits.axes_grid1 import ImageGrid
from sklearn.utils import shuffle
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import activations
from tensorflow.keras.preprocessing import image
from tensorflow.keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Input, concatenate, Dense, Dropout, Activation, Flatten, GaussianNoise, BatchNormalization, GlobalAveragePooling2D, Conv2D, MaxPooling2D
from tensorflow.keras.optimizers import Adam, RMSprop
from tensorflow.keras.applications.vgg19 import VGG19
from tensorflow.keras.applications.inception_v3 import InceptionV3
from tensorflow.keras.applications.resnet50 import ResNet50
from tensorflow.keras.applications.inception_resnet_v2 import InceptionResNetV2
from tensorflow.keras.models import Model
from sklearn.metrics import confusion_matrix
from sklearn.metrics import accuracy_score
from sklearn.metrics import roc_auc_score
from tensorflow.keras.models import model_from_json
from tensorflow.keras import backend as K
from tensorflow.keras.utils import to_categorical
from tf_keras_vis.gradcam import Gradcam
from tf_keras_vis.saliency import Saliency
from tf_keras_vis.utils import normalize
from sklearn.metrics import classification_report
In [2]:
# Define image size
mpl.rcParams['figure.figsize'] = (20,24)

FIRST PART: DATA INGESTION

Data description

After having trained and validated our CNNs, we will test them with the test data:

-338 normal MRI images from 17 control patients

-242 MRI images of diffuse malformations of cortical development from 14 patients

-186 MRI images of periventricular nodular heterotopia (PVNH) from 6 patients

Import original images

In [3]:
# Unzip files
!unzip ~/data/Controltest.zip -d ~/data/
!unzip ~/data/CMtest.zip -d ~/data/
!unzip ~/data/PVNHtest.zip -d ~/data/

# Remove the zipped files
!rm ~/data/Controltest.zip    
!rm ~/data/CMtest.zip  
!rm ~/data/PVNHtest.zip  
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  inflating: /home/ubuntu/data/PVNHtest/6.2_AX T2_30.jpg  
  inflating: /home/ubuntu/data/PVNHtest/6.20_COR MPR RECONS_76.jpg  
  inflating: /home/ubuntu/data/PVNHtest/6.21_COR MPR RECONS_79.jpg  
  inflating: /home/ubuntu/data/PVNHtest/6.3_AX T2_31.jpg  
  inflating: /home/ubuntu/data/PVNHtest/6.4_AX T2 FLAIR FS_19.jpg  
  inflating: /home/ubuntu/data/PVNHtest/6.5_AX T2 FLAIR FS_19.jpg  
  inflating: /home/ubuntu/data/PVNHtest/6.6_COR T2_21.jpg  
  inflating: /home/ubuntu/data/PVNHtest/6.7_COR T2_23.jpg  
  inflating: /home/ubuntu/data/PVNHtest/6.8_COR T2_25.jpg  
  inflating: /home/ubuntu/data/PVNHtest/6.9_COR T2_27.jpg  

Paths to original and processed images

In [4]:
# Path to the folder with the original images
pathtoimagesControltest = './data/Controltest/'

pathtoimagesCMtest = './data/CMtest/'

pathtoimagesPVNHtest = './data/PVNHtest/'


# Create directories to save the processed images
! mkdir ~/data/processedControltest 

! mkdir ~/data/processedCMtest 

! mkdir ~/data/processedPVNHtest 


# Path to the folder with the processed images
pathtoprocessedimagesControltest = './data/processedControltest/'

pathtoprocessedimagesCMtest = './data/processedCMtest/'

pathtoprocessedimagesPVNHtest = './data/processedPVNHtest/'

Read in and preprocess Controltest images

In [5]:
# Define the image size
image_size = (512, 512)

# Read in the training images
Controltest_dir = pathtoimagesControltest
Controltest_files = os.listdir(Controltest_dir)
# For each image
for f in Controltest_files:
    # Open the image
    img = Image.open(Controltest_dir + f)
    # Resize the image so that it has a size 512x512
    img = img.resize(image_size)
    # Transform into a numpy array with no page number and save it into the preprocessed folder
    img_arr = np.array(img)
    img_arr[462:512, 0:100, :] = np.mean(img_arr[452:462, 0:100, :])
    processed_img = Image.fromarray(img_arr, 'RGB')
    processed_img_name = './data/processedControltest/'+'processed'+str(np.random.randint(low=1, high=1e8))+ \
    str(np.random.randint(low=1e4, high=1e6))+str(np.random.randint(low=1e4, high=1e6))+ \
    str(np.random.randint(low=1e4, high=1e6))+str(np.random.randint(low=1e5, high=1e8))+ \
    str(np.random.randint(low=1e2, high=1e7))+str(np.random.randint(low=1e3, high=1e5))+ \
    str(np.random.randint(low=1e2, high=1e8))+'.jpg'
    processed_img.save(processed_img_name)

Read in and preprocess CMtest images

In [6]:
# Define the image size
image_size = (512, 512)

# Read in the training images
CMtest_dir = pathtoimagesCMtest
CMtest_files = os.listdir(CMtest_dir)
# For each image
for f in CMtest_files:
    # Open the image
    img = Image.open(CMtest_dir + f)
    # Resize the image so that it has a size 512x512
    img = img.resize(image_size)
    # Transform into a numpy array with no page number and save it into the preprocessed folder
    img_arr = np.array(img)
    img_arr[462:512, 0:100, :] = np.mean(img_arr[452:462, 0:100, :])
    processed_img = Image.fromarray(img_arr, 'RGB')
    processed_img_name = './data/processedCMtest/'+'processed'+str(np.random.randint(low=1, high=1e8))+ \
    str(np.random.randint(low=1e4, high=1e6))+str(np.random.randint(low=1e4, high=1e6))+ \
    str(np.random.randint(low=1e4, high=1e6))+str(np.random.randint(low=1e5, high=1e8))+ \
    str(np.random.randint(low=1e2, high=1e7))+str(np.random.randint(low=1e3, high=1e5))+ \
    str(np.random.randint(low=1e2, high=1e8))+'.jpg'
    processed_img.save(processed_img_name)  

Read in and preprocess PVNHtest images

In [7]:
# Define the image size
image_size = (512, 512)

# Read in the training images
PVNHtest_dir = pathtoimagesPVNHtest
PVNHtest_files = os.listdir(PVNHtest_dir)
# For each image
for f in PVNHtest_files:
    # Open the image
    img = Image.open(PVNHtest_dir + f)
    # Resize the image so that it has a size 512x512
    img = img.resize(image_size)
    # Transform into a numpy array with no page number and save it into the preprocessed folder
    img_arr = np.array(img)
    img_arr[462:512, 0:100, :] = np.mean(img_arr[452:462, 0:100, :])
    processed_img = Image.fromarray(img_arr, 'RGB')
    processed_img_name = './data/processedPVNHtest/'+'processed'+str(np.random.randint(low=1, high=1e8))+ \
    str(np.random.randint(low=1e4, high=1e6))+str(np.random.randint(low=1e4, high=1e6))+ \
    str(np.random.randint(low=1e4, high=1e6))+str(np.random.randint(low=1e5, high=1e8))+ \
    str(np.random.randint(low=1e2, high=1e7))+str(np.random.randint(low=1e3, high=1e5))+ \
    str(np.random.randint(low=1e2, high=1e8))+'.jpg'
    processed_img.save(processed_img_name)  

SECOND PART: IMPORTATION OF FINAL DATA

Path to the final images

In [8]:
# Create directories for the final images
!mkdir ~/data/FinalControltest 

!mkdir ~/data/FinalCMtest

!mkdir ~/data/FinalPVNHtest 
In [9]:
# Copy all processed images to the final folders
!cp ./data/processedControltest/* ./data/FinalControltest/

!cp ./data/processedCMtest/* ./data/FinalCMtest/

!cp ./data/processedPVNHtest/* ./data/FinalPVNHtest/
In [10]:
## Path to final images
pathtofinalControltest = './data/FinalControltest/'

pathtofinalCMtest = './data/FinalCMtest/'

pathtofinalPVNHtest = './data/FinalPVNHtest/'

Import images and labels for the test set

In [11]:
## CONTROLS

# Define the image size
image_size = (512, 512)

# Read in the test images for controls
Controltest_images = []
Controltest_dir = pathtofinalControltest
Controltest_files = os.listdir(Controltest_dir)
# For each image
for f in Controltest_files:
    # Open the image
    img = Image.open(Controltest_dir + f)
    # Resize the image so that it has a size 512x512
    img = img.resize(image_size)
    # Transform into a numpy array
    img_arr = np.array(img)
    # Add the image to the array of images      
    Controltest_images.append(img_arr)

# After having transformed all images, transform the list into a numpy array  
Controltest_X = np.array(Controltest_images)

# Create an array of labels (0 for controls)
Controltest_y = np.array([[0]*Controltest_X.shape[0]]).T




## DIFFUSE CM

# Read in the test images for CM
CMtest_images = []
CMtest_dir = pathtofinalCMtest
CMtest_files = os.listdir(CMtest_dir)
# For each image
for f in CMtest_files:
    # Open the image
    img = Image.open(CMtest_dir + f)
    # Resize the image so that it has a size 512x512
    img = img.resize(image_size)
    # Transform into a numpy array
    img_arr = np.array(img)
    # Add the image to the array of images      
    CMtest_images.append(img_arr)

# After having transformed all images, transform the list into a numpy array  
CMtest_X = np.array(CMtest_images)

# Create an array of labels (1 for CM)
CMtest_y = np.array([[1]*CMtest_X.shape[0]]).T




## PVNH

# Read in the test images for PVNH
PVNHtest_images = []
PVNHtest_dir = pathtofinalPVNHtest
PVNHtest_files = os.listdir(PVNHtest_dir)
# For each image
for f in PVNHtest_files:
    # Open the image
    img = Image.open(PVNHtest_dir + f)
    # Resize the image so that it has a size 512x512
    img = img.resize(image_size)
    # Transform into a numpy array
    img_arr = np.array(img)
    # Add the image to the array of images      
    PVNHtest_images.append(img_arr)

# After having transformed all images, transform the list into a numpy array  
PVNHtest_X = np.array(PVNHtest_images)

# Create an array of labels (2 for PVNH)
PVNHtest_y = np.array([[2]*PVNHtest_X.shape[0]]).T




## MERGE CONTROLS, DIFFUSE CM, AND PVNH

# Train merge files
test_X = np.concatenate([Controltest_X, CMtest_X, PVNHtest_X])
test_y = np.vstack((Controltest_y, CMtest_y, PVNHtest_y))

# GPU expects values to be 32-bit floats
test_X = test_X.astype(np.float32)

# Rescale the pixel values to be between 0 and 1
test_X /= 255.
In [12]:
# Shuffle in unison the test_X and the test_y array (123 is just a random number for reproducibility)
shuffled_test_X, shuffled_test_y = shuffle(test_X, test_y, random_state=123)

# Transform outcome to one-hot encoding
shuffled_test_y = to_categorical(shuffled_test_y)
In [13]:
# Make sure that the dimensions are as expected
shuffled_test_X.shape
Out[13]:
(766, 512, 512, 3)
In [14]:
# Example of an image to make sure they were converted right
plt.imshow(shuffled_test_X[0])
plt.grid(b=None)
plt.xticks([])
plt.yticks([])
plt.show()
In [15]:
# Make sure that the dimensions are as expected
shuffled_test_y.shape
Out[15]:
(766, 3)
In [16]:
# Make sure that the label is correct for the image
shuffled_test_y[0]
Out[16]:
array([1., 0., 0.], dtype=float32)

THIRD PART: EVALUATE THE NEURAL NETWORK

Load the model

In [17]:
# load model
json_file = open('InceptionResNetV2.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
model = model_from_json(loaded_model_json)
# load weights into new model
model.load_weights("InceptionResNetV2.h5")

Compile the model

In [18]:
# Compile model
model.compile(optimizer = Adam(lr = 0.00025), loss = 'categorical_crossentropy', metrics = ['accuracy'])

Evaluate the model

In [19]:
# Generate predictions in the form of probabilities for the test set
testInceptionResNetV2 = model.predict(shuffled_test_X, batch_size = 32)

# Generate the confusion matrix in the test set
y_true = np.argmax(shuffled_test_y, axis=1)
y_predInceptionResNetV2 = np.argmax(testInceptionResNetV2, axis=1)

# Confusion matrix
pd.DataFrame(confusion_matrix(y_true, y_predInceptionResNetV2), index=['True: Normal', 'True: Diffuse CM', 'True: PVNH'], columns=['Prediction: Normal', 'Prediction: Diffuse CM', 'Prediction: PVNH']).T
Out[19]:
True: Normal True: Diffuse CM True: PVNH
Prediction: Normal 295 34 27
Prediction: Diffuse CM 20 126 11
Prediction: PVNH 23 82 148
In [20]:
# Calculate accuracy in the test set
accuracy_InceptionResNetV2 = accuracy_score(y_true=y_true, y_pred=y_predInceptionResNetV2)
print('The accuracy in the test set is {:.4f}.'.format(accuracy_InceptionResNetV2))
The accuracy in the test set is 0.7428.
In [21]:
# Calculate AUC in the test set
auc_validInceptionResNetV2 = roc_auc_score(shuffled_test_y, model.predict(shuffled_test_X))
print('The AUC in the test set is {:.4f}.'.format(auc_validInceptionResNetV2))
The AUC in the test set is 0.8776.
In [22]:
# Classification report
print(classification_report(y_true, y_predInceptionResNetV2, target_names=['Normal MRI', 'Diffuse CM', 'PVNH']))
              precision    recall  f1-score   support

  Normal MRI       0.83      0.87      0.85       338
  Diffuse CM       0.80      0.52      0.63       242
        PVNH       0.58      0.80      0.67       186

    accuracy                           0.74       766
   macro avg       0.74      0.73      0.72       766
weighted avg       0.76      0.74      0.74       766

Model visualization

In [23]:
# Visualize the structure and layers of the model
model.layers
Out[23]:
[<tensorflow.python.keras.engine.input_layer.InputLayer at 0x7f3fc1ccafd0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3ef02f89e8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1cda828>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1cdac18>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1cdadd8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c91048>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c91208>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c913c8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c915f8>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c917b8>,
 <tensorflow.python.keras.layers.pooling.MaxPooling2D at 0x7f3fc1c919e8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c91b70>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c91da0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c91f60>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c921d0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c92400>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c925f8>,
 <tensorflow.python.keras.layers.pooling.MaxPooling2D at 0x7f3fc1c92828>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c929b0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c92be0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c92da0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c92fd0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c26240>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c26470>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c26668>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c269b0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c26be0>,
 <tensorflow.python.keras.layers.pooling.AveragePooling2D at 0x7f3fc1c26cc0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c26e48>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c2f0b8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c2f2e8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c2f518>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c2f748>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c2f908>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c2fc50>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c2ff98>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c3a320>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c3a550>,
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 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c3a710>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc1c3a7f0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c3a9e8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c3abe0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c3add8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c44048>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c44278>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c444a8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c446a0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c449e8>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c44c18>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c44cf8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c44f28>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c50198>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c503c8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c505c0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c50908>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c50c50>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c50e80>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c50f60>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc1c5a080>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c5a160>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3ee8cb1a90>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c5a6a0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c5a940>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c5ab70>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c5ad30>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c5af60>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1be61d0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1be6400>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1be65f8>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1be6940>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1be6b70>,
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 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1bf20f0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1bf2320>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1bf2518>,
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 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1bf2dd8>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1bf2eb8>,
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 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1bfd0b8>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3fc1bfd358>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1bfd470>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1bfd588>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1bfd7b8>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1bfd978>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1bfdba8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1bfddd8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c06048>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c06240>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c06588>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c067b8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c06898>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c06ac8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c06cf8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c06f28>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c10160>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c104a8>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c107f0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c10a20>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c10b00>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc1c10be0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c10cc0>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3fc1c10f60>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c1c0b8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c1c1d0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1c1c400>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1c1c5c0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c1c7f0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1c1ca20>,
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 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1ba61d0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1ba6400>,
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 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1ba6710>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1ba6940>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1ba6b70>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1ba6d68>,
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 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1bb1438>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1bb1668>,
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 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18fc080>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18fc2b0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18fc470>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18fc6a0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18fc8d0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18fcac8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18fccf8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18fcf28>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1904198>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1904390>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc19046d8>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1904908>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc19049e8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1904ac8>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3fc1904d30>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1904e48>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1904f60>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc19111d0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1911390>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc19115c0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc19117f0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc19119e8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1911c18>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1911e48>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc191d0b8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc191d2b0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc191d5f8>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc191d828>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc191d908>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc191d9e8>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3fc191dc50>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc191dd68>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc191de80>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18a60f0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18a62b0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18a64e0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18a6710>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18a6908>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18a6b38>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18a6d68>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18a6f98>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18b01d0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18b0518>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18b0748>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc18b0828>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18b0908>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3fc18b0b70>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18b0c88>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18b0da0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18b0fd0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18be1d0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18be400>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18be630>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18be828>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18bea58>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18bec88>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18beeb8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18ca0f0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18ca438>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18ca668>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc18ca748>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18ca828>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3fc18caa90>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18caba8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18cacc0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18caef0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18d30f0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18d3320>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18d3550>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18d3748>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18d3978>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18d3ba8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18d3dd8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18d3fd0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18df358>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18df588>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc18df668>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18df748>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3fc18df9b0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18dfac8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18dfbe0>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18dfe10>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18dffd0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc186b240>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc186b470>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc186b668>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc186b898>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc186bac8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc186bcf8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc186bef0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1874278>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18744a8>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc1874588>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1874668>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3fc18748d0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18749e8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1874b00>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1874d30>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1874ef0>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1882160>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1882390>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc1882588>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18827b8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18829e8>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1882c18>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1882e10>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc188c198>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc188c3c8>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc188c4a8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc188c588>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3fc188c7f0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc188c908>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc188ca20>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc188cc50>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc188ce10>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1895080>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18952b0>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18954a8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18956d8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc1895908>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1895b38>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc1895d30>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18a00b8>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18a02e8>,
 <tensorflow.python.keras.layers.merge.Concatenate at 0x7f3fc18a03c8>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18a04a8>,
 <tensorflow.python.keras.layers.core.Lambda at 0x7f3fc18a0710>,
 <tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f3fc18a0828>,
 <tensorflow.python.keras.layers.normalization.BatchNormalization at 0x7f3fc18a0a90>,
 <tensorflow.python.keras.layers.core.Activation at 0x7f3fc18a0c50>,
 <tensorflow.python.keras.layers.pooling.GlobalAveragePooling2D at 0x7f3fc18a0e80>,
 <tensorflow.python.keras.layers.core.Dense at 0x7f3fc18a0f98>,
 <tensorflow.python.keras.layers.core.Dropout at 0x7f3fc182c1d0>,
 <tensorflow.python.keras.layers.core.Dense at 0x7f3fc182c2b0>,
 <tensorflow.python.keras.layers.core.Dropout at 0x7f3fc182c4e0>,
 <tensorflow.python.keras.layers.core.Dense at 0x7f3fc182c5c0>,
 <tensorflow.python.keras.layers.core.Dense at 0x7f3fc182c7f0>]
In [24]:
# Visualize the structure and layers of the model
print(model.summary())
Model: "model_183"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_4 (InputLayer)            [(None, 512, 512, 3) 0                                            
__________________________________________________________________________________________________
conv2d_129 (Conv2D)             (None, 255, 255, 32) 864         input_4[0][0]                    
__________________________________________________________________________________________________
batch_normalization_98 (BatchNo (None, 255, 255, 32) 96          conv2d_129[0][0]                 
__________________________________________________________________________________________________
activation_98 (Activation)      (None, 255, 255, 32) 0           batch_normalization_98[0][0]     
__________________________________________________________________________________________________
conv2d_130 (Conv2D)             (None, 253, 253, 32) 9216        activation_98[0][0]              
__________________________________________________________________________________________________
batch_normalization_99 (BatchNo (None, 253, 253, 32) 96          conv2d_130[0][0]                 
__________________________________________________________________________________________________
activation_99 (Activation)      (None, 253, 253, 32) 0           batch_normalization_99[0][0]     
__________________________________________________________________________________________________
conv2d_131 (Conv2D)             (None, 253, 253, 64) 18432       activation_99[0][0]              
__________________________________________________________________________________________________
batch_normalization_100 (BatchN (None, 253, 253, 64) 192         conv2d_131[0][0]                 
__________________________________________________________________________________________________
activation_100 (Activation)     (None, 253, 253, 64) 0           batch_normalization_100[0][0]    
__________________________________________________________________________________________________
max_pooling2d_14 (MaxPooling2D) (None, 126, 126, 64) 0           activation_100[0][0]             
__________________________________________________________________________________________________
conv2d_132 (Conv2D)             (None, 126, 126, 80) 5120        max_pooling2d_14[0][0]           
__________________________________________________________________________________________________
batch_normalization_101 (BatchN (None, 126, 126, 80) 240         conv2d_132[0][0]                 
__________________________________________________________________________________________________
activation_101 (Activation)     (None, 126, 126, 80) 0           batch_normalization_101[0][0]    
__________________________________________________________________________________________________
conv2d_133 (Conv2D)             (None, 124, 124, 192 138240      activation_101[0][0]             
__________________________________________________________________________________________________
batch_normalization_102 (BatchN (None, 124, 124, 192 576         conv2d_133[0][0]                 
__________________________________________________________________________________________________
activation_102 (Activation)     (None, 124, 124, 192 0           batch_normalization_102[0][0]    
__________________________________________________________________________________________________
max_pooling2d_15 (MaxPooling2D) (None, 61, 61, 192)  0           activation_102[0][0]             
__________________________________________________________________________________________________
conv2d_137 (Conv2D)             (None, 61, 61, 64)   12288       max_pooling2d_15[0][0]           
__________________________________________________________________________________________________
batch_normalization_106 (BatchN (None, 61, 61, 64)   192         conv2d_137[0][0]                 
__________________________________________________________________________________________________
activation_106 (Activation)     (None, 61, 61, 64)   0           batch_normalization_106[0][0]    
__________________________________________________________________________________________________
conv2d_135 (Conv2D)             (None, 61, 61, 48)   9216        max_pooling2d_15[0][0]           
__________________________________________________________________________________________________
conv2d_138 (Conv2D)             (None, 61, 61, 96)   55296       activation_106[0][0]             
__________________________________________________________________________________________________
batch_normalization_104 (BatchN (None, 61, 61, 48)   144         conv2d_135[0][0]                 
__________________________________________________________________________________________________
batch_normalization_107 (BatchN (None, 61, 61, 96)   288         conv2d_138[0][0]                 
__________________________________________________________________________________________________
activation_104 (Activation)     (None, 61, 61, 48)   0           batch_normalization_104[0][0]    
__________________________________________________________________________________________________
activation_107 (Activation)     (None, 61, 61, 96)   0           batch_normalization_107[0][0]    
__________________________________________________________________________________________________
average_pooling2d_9 (AveragePoo (None, 61, 61, 192)  0           max_pooling2d_15[0][0]           
__________________________________________________________________________________________________
conv2d_134 (Conv2D)             (None, 61, 61, 96)   18432       max_pooling2d_15[0][0]           
__________________________________________________________________________________________________
conv2d_136 (Conv2D)             (None, 61, 61, 64)   76800       activation_104[0][0]             
__________________________________________________________________________________________________
conv2d_139 (Conv2D)             (None, 61, 61, 96)   82944       activation_107[0][0]             
__________________________________________________________________________________________________
conv2d_140 (Conv2D)             (None, 61, 61, 64)   12288       average_pooling2d_9[0][0]        
__________________________________________________________________________________________________
batch_normalization_103 (BatchN (None, 61, 61, 96)   288         conv2d_134[0][0]                 
__________________________________________________________________________________________________
batch_normalization_105 (BatchN (None, 61, 61, 64)   192         conv2d_136[0][0]                 
__________________________________________________________________________________________________
batch_normalization_108 (BatchN (None, 61, 61, 96)   288         conv2d_139[0][0]                 
__________________________________________________________________________________________________
batch_normalization_109 (BatchN (None, 61, 61, 64)   192         conv2d_140[0][0]                 
__________________________________________________________________________________________________
activation_103 (Activation)     (None, 61, 61, 96)   0           batch_normalization_103[0][0]    
__________________________________________________________________________________________________
activation_105 (Activation)     (None, 61, 61, 64)   0           batch_normalization_105[0][0]    
__________________________________________________________________________________________________
activation_108 (Activation)     (None, 61, 61, 96)   0           batch_normalization_108[0][0]    
__________________________________________________________________________________________________
activation_109 (Activation)     (None, 61, 61, 64)   0           batch_normalization_109[0][0]    
__________________________________________________________________________________________________
mixed_5b (Concatenate)          (None, 61, 61, 320)  0           activation_103[0][0]             
                                                                 activation_105[0][0]             
                                                                 activation_108[0][0]             
                                                                 activation_109[0][0]             
__________________________________________________________________________________________________
conv2d_144 (Conv2D)             (None, 61, 61, 32)   10240       mixed_5b[0][0]                   
__________________________________________________________________________________________________
batch_normalization_113 (BatchN (None, 61, 61, 32)   96          conv2d_144[0][0]                 
__________________________________________________________________________________________________
activation_113 (Activation)     (None, 61, 61, 32)   0           batch_normalization_113[0][0]    
__________________________________________________________________________________________________
conv2d_142 (Conv2D)             (None, 61, 61, 32)   10240       mixed_5b[0][0]                   
__________________________________________________________________________________________________
conv2d_145 (Conv2D)             (None, 61, 61, 48)   13824       activation_113[0][0]             
__________________________________________________________________________________________________
batch_normalization_111 (BatchN (None, 61, 61, 32)   96          conv2d_142[0][0]                 
__________________________________________________________________________________________________
batch_normalization_114 (BatchN (None, 61, 61, 48)   144         conv2d_145[0][0]                 
__________________________________________________________________________________________________
activation_111 (Activation)     (None, 61, 61, 32)   0           batch_normalization_111[0][0]    
__________________________________________________________________________________________________
activation_114 (Activation)     (None, 61, 61, 48)   0           batch_normalization_114[0][0]    
__________________________________________________________________________________________________
conv2d_141 (Conv2D)             (None, 61, 61, 32)   10240       mixed_5b[0][0]                   
__________________________________________________________________________________________________
conv2d_143 (Conv2D)             (None, 61, 61, 32)   9216        activation_111[0][0]             
__________________________________________________________________________________________________
conv2d_146 (Conv2D)             (None, 61, 61, 64)   27648       activation_114[0][0]             
__________________________________________________________________________________________________
batch_normalization_110 (BatchN (None, 61, 61, 32)   96          conv2d_141[0][0]                 
__________________________________________________________________________________________________
batch_normalization_112 (BatchN (None, 61, 61, 32)   96          conv2d_143[0][0]                 
__________________________________________________________________________________________________
batch_normalization_115 (BatchN (None, 61, 61, 64)   192         conv2d_146[0][0]                 
__________________________________________________________________________________________________
activation_110 (Activation)     (None, 61, 61, 32)   0           batch_normalization_110[0][0]    
__________________________________________________________________________________________________
activation_112 (Activation)     (None, 61, 61, 32)   0           batch_normalization_112[0][0]    
__________________________________________________________________________________________________
activation_115 (Activation)     (None, 61, 61, 64)   0           batch_normalization_115[0][0]    
__________________________________________________________________________________________________
block35_1_mixed (Concatenate)   (None, 61, 61, 128)  0           activation_110[0][0]             
                                                                 activation_112[0][0]             
                                                                 activation_115[0][0]             
__________________________________________________________________________________________________
block35_1_conv (Conv2D)         (None, 61, 61, 320)  41280       block35_1_mixed[0][0]            
__________________________________________________________________________________________________
block35_1 (Lambda)              (None, 61, 61, 320)  0           mixed_5b[0][0]                   
                                                                 block35_1_conv[0][0]             
__________________________________________________________________________________________________
block35_1_ac (Activation)       (None, 61, 61, 320)  0           block35_1[0][0]                  
__________________________________________________________________________________________________
conv2d_150 (Conv2D)             (None, 61, 61, 32)   10240       block35_1_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_119 (BatchN (None, 61, 61, 32)   96          conv2d_150[0][0]                 
__________________________________________________________________________________________________
activation_119 (Activation)     (None, 61, 61, 32)   0           batch_normalization_119[0][0]    
__________________________________________________________________________________________________
conv2d_148 (Conv2D)             (None, 61, 61, 32)   10240       block35_1_ac[0][0]               
__________________________________________________________________________________________________
conv2d_151 (Conv2D)             (None, 61, 61, 48)   13824       activation_119[0][0]             
__________________________________________________________________________________________________
batch_normalization_117 (BatchN (None, 61, 61, 32)   96          conv2d_148[0][0]                 
__________________________________________________________________________________________________
batch_normalization_120 (BatchN (None, 61, 61, 48)   144         conv2d_151[0][0]                 
__________________________________________________________________________________________________
activation_117 (Activation)     (None, 61, 61, 32)   0           batch_normalization_117[0][0]    
__________________________________________________________________________________________________
activation_120 (Activation)     (None, 61, 61, 48)   0           batch_normalization_120[0][0]    
__________________________________________________________________________________________________
conv2d_147 (Conv2D)             (None, 61, 61, 32)   10240       block35_1_ac[0][0]               
__________________________________________________________________________________________________
conv2d_149 (Conv2D)             (None, 61, 61, 32)   9216        activation_117[0][0]             
__________________________________________________________________________________________________
conv2d_152 (Conv2D)             (None, 61, 61, 64)   27648       activation_120[0][0]             
__________________________________________________________________________________________________
batch_normalization_116 (BatchN (None, 61, 61, 32)   96          conv2d_147[0][0]                 
__________________________________________________________________________________________________
batch_normalization_118 (BatchN (None, 61, 61, 32)   96          conv2d_149[0][0]                 
__________________________________________________________________________________________________
batch_normalization_121 (BatchN (None, 61, 61, 64)   192         conv2d_152[0][0]                 
__________________________________________________________________________________________________
activation_116 (Activation)     (None, 61, 61, 32)   0           batch_normalization_116[0][0]    
__________________________________________________________________________________________________
activation_118 (Activation)     (None, 61, 61, 32)   0           batch_normalization_118[0][0]    
__________________________________________________________________________________________________
activation_121 (Activation)     (None, 61, 61, 64)   0           batch_normalization_121[0][0]    
__________________________________________________________________________________________________
block35_2_mixed (Concatenate)   (None, 61, 61, 128)  0           activation_116[0][0]             
                                                                 activation_118[0][0]             
                                                                 activation_121[0][0]             
__________________________________________________________________________________________________
block35_2_conv (Conv2D)         (None, 61, 61, 320)  41280       block35_2_mixed[0][0]            
__________________________________________________________________________________________________
block35_2 (Lambda)              (None, 61, 61, 320)  0           block35_1_ac[0][0]               
                                                                 block35_2_conv[0][0]             
__________________________________________________________________________________________________
block35_2_ac (Activation)       (None, 61, 61, 320)  0           block35_2[0][0]                  
__________________________________________________________________________________________________
conv2d_156 (Conv2D)             (None, 61, 61, 32)   10240       block35_2_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_125 (BatchN (None, 61, 61, 32)   96          conv2d_156[0][0]                 
__________________________________________________________________________________________________
activation_125 (Activation)     (None, 61, 61, 32)   0           batch_normalization_125[0][0]    
__________________________________________________________________________________________________
conv2d_154 (Conv2D)             (None, 61, 61, 32)   10240       block35_2_ac[0][0]               
__________________________________________________________________________________________________
conv2d_157 (Conv2D)             (None, 61, 61, 48)   13824       activation_125[0][0]             
__________________________________________________________________________________________________
batch_normalization_123 (BatchN (None, 61, 61, 32)   96          conv2d_154[0][0]                 
__________________________________________________________________________________________________
batch_normalization_126 (BatchN (None, 61, 61, 48)   144         conv2d_157[0][0]                 
__________________________________________________________________________________________________
activation_123 (Activation)     (None, 61, 61, 32)   0           batch_normalization_123[0][0]    
__________________________________________________________________________________________________
activation_126 (Activation)     (None, 61, 61, 48)   0           batch_normalization_126[0][0]    
__________________________________________________________________________________________________
conv2d_153 (Conv2D)             (None, 61, 61, 32)   10240       block35_2_ac[0][0]               
__________________________________________________________________________________________________
conv2d_155 (Conv2D)             (None, 61, 61, 32)   9216        activation_123[0][0]             
__________________________________________________________________________________________________
conv2d_158 (Conv2D)             (None, 61, 61, 64)   27648       activation_126[0][0]             
__________________________________________________________________________________________________
batch_normalization_122 (BatchN (None, 61, 61, 32)   96          conv2d_153[0][0]                 
__________________________________________________________________________________________________
batch_normalization_124 (BatchN (None, 61, 61, 32)   96          conv2d_155[0][0]                 
__________________________________________________________________________________________________
batch_normalization_127 (BatchN (None, 61, 61, 64)   192         conv2d_158[0][0]                 
__________________________________________________________________________________________________
activation_122 (Activation)     (None, 61, 61, 32)   0           batch_normalization_122[0][0]    
__________________________________________________________________________________________________
activation_124 (Activation)     (None, 61, 61, 32)   0           batch_normalization_124[0][0]    
__________________________________________________________________________________________________
activation_127 (Activation)     (None, 61, 61, 64)   0           batch_normalization_127[0][0]    
__________________________________________________________________________________________________
block35_3_mixed (Concatenate)   (None, 61, 61, 128)  0           activation_122[0][0]             
                                                                 activation_124[0][0]             
                                                                 activation_127[0][0]             
__________________________________________________________________________________________________
block35_3_conv (Conv2D)         (None, 61, 61, 320)  41280       block35_3_mixed[0][0]            
__________________________________________________________________________________________________
block35_3 (Lambda)              (None, 61, 61, 320)  0           block35_2_ac[0][0]               
                                                                 block35_3_conv[0][0]             
__________________________________________________________________________________________________
block35_3_ac (Activation)       (None, 61, 61, 320)  0           block35_3[0][0]                  
__________________________________________________________________________________________________
conv2d_162 (Conv2D)             (None, 61, 61, 32)   10240       block35_3_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_131 (BatchN (None, 61, 61, 32)   96          conv2d_162[0][0]                 
__________________________________________________________________________________________________
activation_131 (Activation)     (None, 61, 61, 32)   0           batch_normalization_131[0][0]    
__________________________________________________________________________________________________
conv2d_160 (Conv2D)             (None, 61, 61, 32)   10240       block35_3_ac[0][0]               
__________________________________________________________________________________________________
conv2d_163 (Conv2D)             (None, 61, 61, 48)   13824       activation_131[0][0]             
__________________________________________________________________________________________________
batch_normalization_129 (BatchN (None, 61, 61, 32)   96          conv2d_160[0][0]                 
__________________________________________________________________________________________________
batch_normalization_132 (BatchN (None, 61, 61, 48)   144         conv2d_163[0][0]                 
__________________________________________________________________________________________________
activation_129 (Activation)     (None, 61, 61, 32)   0           batch_normalization_129[0][0]    
__________________________________________________________________________________________________
activation_132 (Activation)     (None, 61, 61, 48)   0           batch_normalization_132[0][0]    
__________________________________________________________________________________________________
conv2d_159 (Conv2D)             (None, 61, 61, 32)   10240       block35_3_ac[0][0]               
__________________________________________________________________________________________________
conv2d_161 (Conv2D)             (None, 61, 61, 32)   9216        activation_129[0][0]             
__________________________________________________________________________________________________
conv2d_164 (Conv2D)             (None, 61, 61, 64)   27648       activation_132[0][0]             
__________________________________________________________________________________________________
batch_normalization_128 (BatchN (None, 61, 61, 32)   96          conv2d_159[0][0]                 
__________________________________________________________________________________________________
batch_normalization_130 (BatchN (None, 61, 61, 32)   96          conv2d_161[0][0]                 
__________________________________________________________________________________________________
batch_normalization_133 (BatchN (None, 61, 61, 64)   192         conv2d_164[0][0]                 
__________________________________________________________________________________________________
activation_128 (Activation)     (None, 61, 61, 32)   0           batch_normalization_128[0][0]    
__________________________________________________________________________________________________
activation_130 (Activation)     (None, 61, 61, 32)   0           batch_normalization_130[0][0]    
__________________________________________________________________________________________________
activation_133 (Activation)     (None, 61, 61, 64)   0           batch_normalization_133[0][0]    
__________________________________________________________________________________________________
block35_4_mixed (Concatenate)   (None, 61, 61, 128)  0           activation_128[0][0]             
                                                                 activation_130[0][0]             
                                                                 activation_133[0][0]             
__________________________________________________________________________________________________
block35_4_conv (Conv2D)         (None, 61, 61, 320)  41280       block35_4_mixed[0][0]            
__________________________________________________________________________________________________
block35_4 (Lambda)              (None, 61, 61, 320)  0           block35_3_ac[0][0]               
                                                                 block35_4_conv[0][0]             
__________________________________________________________________________________________________
block35_4_ac (Activation)       (None, 61, 61, 320)  0           block35_4[0][0]                  
__________________________________________________________________________________________________
conv2d_168 (Conv2D)             (None, 61, 61, 32)   10240       block35_4_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_137 (BatchN (None, 61, 61, 32)   96          conv2d_168[0][0]                 
__________________________________________________________________________________________________
activation_137 (Activation)     (None, 61, 61, 32)   0           batch_normalization_137[0][0]    
__________________________________________________________________________________________________
conv2d_166 (Conv2D)             (None, 61, 61, 32)   10240       block35_4_ac[0][0]               
__________________________________________________________________________________________________
conv2d_169 (Conv2D)             (None, 61, 61, 48)   13824       activation_137[0][0]             
__________________________________________________________________________________________________
batch_normalization_135 (BatchN (None, 61, 61, 32)   96          conv2d_166[0][0]                 
__________________________________________________________________________________________________
batch_normalization_138 (BatchN (None, 61, 61, 48)   144         conv2d_169[0][0]                 
__________________________________________________________________________________________________
activation_135 (Activation)     (None, 61, 61, 32)   0           batch_normalization_135[0][0]    
__________________________________________________________________________________________________
activation_138 (Activation)     (None, 61, 61, 48)   0           batch_normalization_138[0][0]    
__________________________________________________________________________________________________
conv2d_165 (Conv2D)             (None, 61, 61, 32)   10240       block35_4_ac[0][0]               
__________________________________________________________________________________________________
conv2d_167 (Conv2D)             (None, 61, 61, 32)   9216        activation_135[0][0]             
__________________________________________________________________________________________________
conv2d_170 (Conv2D)             (None, 61, 61, 64)   27648       activation_138[0][0]             
__________________________________________________________________________________________________
batch_normalization_134 (BatchN (None, 61, 61, 32)   96          conv2d_165[0][0]                 
__________________________________________________________________________________________________
batch_normalization_136 (BatchN (None, 61, 61, 32)   96          conv2d_167[0][0]                 
__________________________________________________________________________________________________
batch_normalization_139 (BatchN (None, 61, 61, 64)   192         conv2d_170[0][0]                 
__________________________________________________________________________________________________
activation_134 (Activation)     (None, 61, 61, 32)   0           batch_normalization_134[0][0]    
__________________________________________________________________________________________________
activation_136 (Activation)     (None, 61, 61, 32)   0           batch_normalization_136[0][0]    
__________________________________________________________________________________________________
activation_139 (Activation)     (None, 61, 61, 64)   0           batch_normalization_139[0][0]    
__________________________________________________________________________________________________
block35_5_mixed (Concatenate)   (None, 61, 61, 128)  0           activation_134[0][0]             
                                                                 activation_136[0][0]             
                                                                 activation_139[0][0]             
__________________________________________________________________________________________________
block35_5_conv (Conv2D)         (None, 61, 61, 320)  41280       block35_5_mixed[0][0]            
__________________________________________________________________________________________________
block35_5 (Lambda)              (None, 61, 61, 320)  0           block35_4_ac[0][0]               
                                                                 block35_5_conv[0][0]             
__________________________________________________________________________________________________
block35_5_ac (Activation)       (None, 61, 61, 320)  0           block35_5[0][0]                  
__________________________________________________________________________________________________
conv2d_174 (Conv2D)             (None, 61, 61, 32)   10240       block35_5_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_143 (BatchN (None, 61, 61, 32)   96          conv2d_174[0][0]                 
__________________________________________________________________________________________________
activation_143 (Activation)     (None, 61, 61, 32)   0           batch_normalization_143[0][0]    
__________________________________________________________________________________________________
conv2d_172 (Conv2D)             (None, 61, 61, 32)   10240       block35_5_ac[0][0]               
__________________________________________________________________________________________________
conv2d_175 (Conv2D)             (None, 61, 61, 48)   13824       activation_143[0][0]             
__________________________________________________________________________________________________
batch_normalization_141 (BatchN (None, 61, 61, 32)   96          conv2d_172[0][0]                 
__________________________________________________________________________________________________
batch_normalization_144 (BatchN (None, 61, 61, 48)   144         conv2d_175[0][0]                 
__________________________________________________________________________________________________
activation_141 (Activation)     (None, 61, 61, 32)   0           batch_normalization_141[0][0]    
__________________________________________________________________________________________________
activation_144 (Activation)     (None, 61, 61, 48)   0           batch_normalization_144[0][0]    
__________________________________________________________________________________________________
conv2d_171 (Conv2D)             (None, 61, 61, 32)   10240       block35_5_ac[0][0]               
__________________________________________________________________________________________________
conv2d_173 (Conv2D)             (None, 61, 61, 32)   9216        activation_141[0][0]             
__________________________________________________________________________________________________
conv2d_176 (Conv2D)             (None, 61, 61, 64)   27648       activation_144[0][0]             
__________________________________________________________________________________________________
batch_normalization_140 (BatchN (None, 61, 61, 32)   96          conv2d_171[0][0]                 
__________________________________________________________________________________________________
batch_normalization_142 (BatchN (None, 61, 61, 32)   96          conv2d_173[0][0]                 
__________________________________________________________________________________________________
batch_normalization_145 (BatchN (None, 61, 61, 64)   192         conv2d_176[0][0]                 
__________________________________________________________________________________________________
activation_140 (Activation)     (None, 61, 61, 32)   0           batch_normalization_140[0][0]    
__________________________________________________________________________________________________
activation_142 (Activation)     (None, 61, 61, 32)   0           batch_normalization_142[0][0]    
__________________________________________________________________________________________________
activation_145 (Activation)     (None, 61, 61, 64)   0           batch_normalization_145[0][0]    
__________________________________________________________________________________________________
block35_6_mixed (Concatenate)   (None, 61, 61, 128)  0           activation_140[0][0]             
                                                                 activation_142[0][0]             
                                                                 activation_145[0][0]             
__________________________________________________________________________________________________
block35_6_conv (Conv2D)         (None, 61, 61, 320)  41280       block35_6_mixed[0][0]            
__________________________________________________________________________________________________
block35_6 (Lambda)              (None, 61, 61, 320)  0           block35_5_ac[0][0]               
                                                                 block35_6_conv[0][0]             
__________________________________________________________________________________________________
block35_6_ac (Activation)       (None, 61, 61, 320)  0           block35_6[0][0]                  
__________________________________________________________________________________________________
conv2d_180 (Conv2D)             (None, 61, 61, 32)   10240       block35_6_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_149 (BatchN (None, 61, 61, 32)   96          conv2d_180[0][0]                 
__________________________________________________________________________________________________
activation_149 (Activation)     (None, 61, 61, 32)   0           batch_normalization_149[0][0]    
__________________________________________________________________________________________________
conv2d_178 (Conv2D)             (None, 61, 61, 32)   10240       block35_6_ac[0][0]               
__________________________________________________________________________________________________
conv2d_181 (Conv2D)             (None, 61, 61, 48)   13824       activation_149[0][0]             
__________________________________________________________________________________________________
batch_normalization_147 (BatchN (None, 61, 61, 32)   96          conv2d_178[0][0]                 
__________________________________________________________________________________________________
batch_normalization_150 (BatchN (None, 61, 61, 48)   144         conv2d_181[0][0]                 
__________________________________________________________________________________________________
activation_147 (Activation)     (None, 61, 61, 32)   0           batch_normalization_147[0][0]    
__________________________________________________________________________________________________
activation_150 (Activation)     (None, 61, 61, 48)   0           batch_normalization_150[0][0]    
__________________________________________________________________________________________________
conv2d_177 (Conv2D)             (None, 61, 61, 32)   10240       block35_6_ac[0][0]               
__________________________________________________________________________________________________
conv2d_179 (Conv2D)             (None, 61, 61, 32)   9216        activation_147[0][0]             
__________________________________________________________________________________________________
conv2d_182 (Conv2D)             (None, 61, 61, 64)   27648       activation_150[0][0]             
__________________________________________________________________________________________________
batch_normalization_146 (BatchN (None, 61, 61, 32)   96          conv2d_177[0][0]                 
__________________________________________________________________________________________________
batch_normalization_148 (BatchN (None, 61, 61, 32)   96          conv2d_179[0][0]                 
__________________________________________________________________________________________________
batch_normalization_151 (BatchN (None, 61, 61, 64)   192         conv2d_182[0][0]                 
__________________________________________________________________________________________________
activation_146 (Activation)     (None, 61, 61, 32)   0           batch_normalization_146[0][0]    
__________________________________________________________________________________________________
activation_148 (Activation)     (None, 61, 61, 32)   0           batch_normalization_148[0][0]    
__________________________________________________________________________________________________
activation_151 (Activation)     (None, 61, 61, 64)   0           batch_normalization_151[0][0]    
__________________________________________________________________________________________________
block35_7_mixed (Concatenate)   (None, 61, 61, 128)  0           activation_146[0][0]             
                                                                 activation_148[0][0]             
                                                                 activation_151[0][0]             
__________________________________________________________________________________________________
block35_7_conv (Conv2D)         (None, 61, 61, 320)  41280       block35_7_mixed[0][0]            
__________________________________________________________________________________________________
block35_7 (Lambda)              (None, 61, 61, 320)  0           block35_6_ac[0][0]               
                                                                 block35_7_conv[0][0]             
__________________________________________________________________________________________________
block35_7_ac (Activation)       (None, 61, 61, 320)  0           block35_7[0][0]                  
__________________________________________________________________________________________________
conv2d_186 (Conv2D)             (None, 61, 61, 32)   10240       block35_7_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_155 (BatchN (None, 61, 61, 32)   96          conv2d_186[0][0]                 
__________________________________________________________________________________________________
activation_155 (Activation)     (None, 61, 61, 32)   0           batch_normalization_155[0][0]    
__________________________________________________________________________________________________
conv2d_184 (Conv2D)             (None, 61, 61, 32)   10240       block35_7_ac[0][0]               
__________________________________________________________________________________________________
conv2d_187 (Conv2D)             (None, 61, 61, 48)   13824       activation_155[0][0]             
__________________________________________________________________________________________________
batch_normalization_153 (BatchN (None, 61, 61, 32)   96          conv2d_184[0][0]                 
__________________________________________________________________________________________________
batch_normalization_156 (BatchN (None, 61, 61, 48)   144         conv2d_187[0][0]                 
__________________________________________________________________________________________________
activation_153 (Activation)     (None, 61, 61, 32)   0           batch_normalization_153[0][0]    
__________________________________________________________________________________________________
activation_156 (Activation)     (None, 61, 61, 48)   0           batch_normalization_156[0][0]    
__________________________________________________________________________________________________
conv2d_183 (Conv2D)             (None, 61, 61, 32)   10240       block35_7_ac[0][0]               
__________________________________________________________________________________________________
conv2d_185 (Conv2D)             (None, 61, 61, 32)   9216        activation_153[0][0]             
__________________________________________________________________________________________________
conv2d_188 (Conv2D)             (None, 61, 61, 64)   27648       activation_156[0][0]             
__________________________________________________________________________________________________
batch_normalization_152 (BatchN (None, 61, 61, 32)   96          conv2d_183[0][0]                 
__________________________________________________________________________________________________
batch_normalization_154 (BatchN (None, 61, 61, 32)   96          conv2d_185[0][0]                 
__________________________________________________________________________________________________
batch_normalization_157 (BatchN (None, 61, 61, 64)   192         conv2d_188[0][0]                 
__________________________________________________________________________________________________
activation_152 (Activation)     (None, 61, 61, 32)   0           batch_normalization_152[0][0]    
__________________________________________________________________________________________________
activation_154 (Activation)     (None, 61, 61, 32)   0           batch_normalization_154[0][0]    
__________________________________________________________________________________________________
activation_157 (Activation)     (None, 61, 61, 64)   0           batch_normalization_157[0][0]    
__________________________________________________________________________________________________
block35_8_mixed (Concatenate)   (None, 61, 61, 128)  0           activation_152[0][0]             
                                                                 activation_154[0][0]             
                                                                 activation_157[0][0]             
__________________________________________________________________________________________________
block35_8_conv (Conv2D)         (None, 61, 61, 320)  41280       block35_8_mixed[0][0]            
__________________________________________________________________________________________________
block35_8 (Lambda)              (None, 61, 61, 320)  0           block35_7_ac[0][0]               
                                                                 block35_8_conv[0][0]             
__________________________________________________________________________________________________
block35_8_ac (Activation)       (None, 61, 61, 320)  0           block35_8[0][0]                  
__________________________________________________________________________________________________
conv2d_192 (Conv2D)             (None, 61, 61, 32)   10240       block35_8_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_161 (BatchN (None, 61, 61, 32)   96          conv2d_192[0][0]                 
__________________________________________________________________________________________________
activation_161 (Activation)     (None, 61, 61, 32)   0           batch_normalization_161[0][0]    
__________________________________________________________________________________________________
conv2d_190 (Conv2D)             (None, 61, 61, 32)   10240       block35_8_ac[0][0]               
__________________________________________________________________________________________________
conv2d_193 (Conv2D)             (None, 61, 61, 48)   13824       activation_161[0][0]             
__________________________________________________________________________________________________
batch_normalization_159 (BatchN (None, 61, 61, 32)   96          conv2d_190[0][0]                 
__________________________________________________________________________________________________
batch_normalization_162 (BatchN (None, 61, 61, 48)   144         conv2d_193[0][0]                 
__________________________________________________________________________________________________
activation_159 (Activation)     (None, 61, 61, 32)   0           batch_normalization_159[0][0]    
__________________________________________________________________________________________________
activation_162 (Activation)     (None, 61, 61, 48)   0           batch_normalization_162[0][0]    
__________________________________________________________________________________________________
conv2d_189 (Conv2D)             (None, 61, 61, 32)   10240       block35_8_ac[0][0]               
__________________________________________________________________________________________________
conv2d_191 (Conv2D)             (None, 61, 61, 32)   9216        activation_159[0][0]             
__________________________________________________________________________________________________
conv2d_194 (Conv2D)             (None, 61, 61, 64)   27648       activation_162[0][0]             
__________________________________________________________________________________________________
batch_normalization_158 (BatchN (None, 61, 61, 32)   96          conv2d_189[0][0]                 
__________________________________________________________________________________________________
batch_normalization_160 (BatchN (None, 61, 61, 32)   96          conv2d_191[0][0]                 
__________________________________________________________________________________________________
batch_normalization_163 (BatchN (None, 61, 61, 64)   192         conv2d_194[0][0]                 
__________________________________________________________________________________________________
activation_158 (Activation)     (None, 61, 61, 32)   0           batch_normalization_158[0][0]    
__________________________________________________________________________________________________
activation_160 (Activation)     (None, 61, 61, 32)   0           batch_normalization_160[0][0]    
__________________________________________________________________________________________________
activation_163 (Activation)     (None, 61, 61, 64)   0           batch_normalization_163[0][0]    
__________________________________________________________________________________________________
block35_9_mixed (Concatenate)   (None, 61, 61, 128)  0           activation_158[0][0]             
                                                                 activation_160[0][0]             
                                                                 activation_163[0][0]             
__________________________________________________________________________________________________
block35_9_conv (Conv2D)         (None, 61, 61, 320)  41280       block35_9_mixed[0][0]            
__________________________________________________________________________________________________
block35_9 (Lambda)              (None, 61, 61, 320)  0           block35_8_ac[0][0]               
                                                                 block35_9_conv[0][0]             
__________________________________________________________________________________________________
block35_9_ac (Activation)       (None, 61, 61, 320)  0           block35_9[0][0]                  
__________________________________________________________________________________________________
conv2d_198 (Conv2D)             (None, 61, 61, 32)   10240       block35_9_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_167 (BatchN (None, 61, 61, 32)   96          conv2d_198[0][0]                 
__________________________________________________________________________________________________
activation_167 (Activation)     (None, 61, 61, 32)   0           batch_normalization_167[0][0]    
__________________________________________________________________________________________________
conv2d_196 (Conv2D)             (None, 61, 61, 32)   10240       block35_9_ac[0][0]               
__________________________________________________________________________________________________
conv2d_199 (Conv2D)             (None, 61, 61, 48)   13824       activation_167[0][0]             
__________________________________________________________________________________________________
batch_normalization_165 (BatchN (None, 61, 61, 32)   96          conv2d_196[0][0]                 
__________________________________________________________________________________________________
batch_normalization_168 (BatchN (None, 61, 61, 48)   144         conv2d_199[0][0]                 
__________________________________________________________________________________________________
activation_165 (Activation)     (None, 61, 61, 32)   0           batch_normalization_165[0][0]    
__________________________________________________________________________________________________
activation_168 (Activation)     (None, 61, 61, 48)   0           batch_normalization_168[0][0]    
__________________________________________________________________________________________________
conv2d_195 (Conv2D)             (None, 61, 61, 32)   10240       block35_9_ac[0][0]               
__________________________________________________________________________________________________
conv2d_197 (Conv2D)             (None, 61, 61, 32)   9216        activation_165[0][0]             
__________________________________________________________________________________________________
conv2d_200 (Conv2D)             (None, 61, 61, 64)   27648       activation_168[0][0]             
__________________________________________________________________________________________________
batch_normalization_164 (BatchN (None, 61, 61, 32)   96          conv2d_195[0][0]                 
__________________________________________________________________________________________________
batch_normalization_166 (BatchN (None, 61, 61, 32)   96          conv2d_197[0][0]                 
__________________________________________________________________________________________________
batch_normalization_169 (BatchN (None, 61, 61, 64)   192         conv2d_200[0][0]                 
__________________________________________________________________________________________________
activation_164 (Activation)     (None, 61, 61, 32)   0           batch_normalization_164[0][0]    
__________________________________________________________________________________________________
activation_166 (Activation)     (None, 61, 61, 32)   0           batch_normalization_166[0][0]    
__________________________________________________________________________________________________
activation_169 (Activation)     (None, 61, 61, 64)   0           batch_normalization_169[0][0]    
__________________________________________________________________________________________________
block35_10_mixed (Concatenate)  (None, 61, 61, 128)  0           activation_164[0][0]             
                                                                 activation_166[0][0]             
                                                                 activation_169[0][0]             
__________________________________________________________________________________________________
block35_10_conv (Conv2D)        (None, 61, 61, 320)  41280       block35_10_mixed[0][0]           
__________________________________________________________________________________________________
block35_10 (Lambda)             (None, 61, 61, 320)  0           block35_9_ac[0][0]               
                                                                 block35_10_conv[0][0]            
__________________________________________________________________________________________________
block35_10_ac (Activation)      (None, 61, 61, 320)  0           block35_10[0][0]                 
__________________________________________________________________________________________________
conv2d_202 (Conv2D)             (None, 61, 61, 256)  81920       block35_10_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_171 (BatchN (None, 61, 61, 256)  768         conv2d_202[0][0]                 
__________________________________________________________________________________________________
activation_171 (Activation)     (None, 61, 61, 256)  0           batch_normalization_171[0][0]    
__________________________________________________________________________________________________
conv2d_203 (Conv2D)             (None, 61, 61, 256)  589824      activation_171[0][0]             
__________________________________________________________________________________________________
batch_normalization_172 (BatchN (None, 61, 61, 256)  768         conv2d_203[0][0]                 
__________________________________________________________________________________________________
activation_172 (Activation)     (None, 61, 61, 256)  0           batch_normalization_172[0][0]    
__________________________________________________________________________________________________
conv2d_201 (Conv2D)             (None, 30, 30, 384)  1105920     block35_10_ac[0][0]              
__________________________________________________________________________________________________
conv2d_204 (Conv2D)             (None, 30, 30, 384)  884736      activation_172[0][0]             
__________________________________________________________________________________________________
batch_normalization_170 (BatchN (None, 30, 30, 384)  1152        conv2d_201[0][0]                 
__________________________________________________________________________________________________
batch_normalization_173 (BatchN (None, 30, 30, 384)  1152        conv2d_204[0][0]                 
__________________________________________________________________________________________________
activation_170 (Activation)     (None, 30, 30, 384)  0           batch_normalization_170[0][0]    
__________________________________________________________________________________________________
activation_173 (Activation)     (None, 30, 30, 384)  0           batch_normalization_173[0][0]    
__________________________________________________________________________________________________
max_pooling2d_16 (MaxPooling2D) (None, 30, 30, 320)  0           block35_10_ac[0][0]              
__________________________________________________________________________________________________
mixed_6a (Concatenate)          (None, 30, 30, 1088) 0           activation_170[0][0]             
                                                                 activation_173[0][0]             
                                                                 max_pooling2d_16[0][0]           
__________________________________________________________________________________________________
conv2d_206 (Conv2D)             (None, 30, 30, 128)  139264      mixed_6a[0][0]                   
__________________________________________________________________________________________________
batch_normalization_175 (BatchN (None, 30, 30, 128)  384         conv2d_206[0][0]                 
__________________________________________________________________________________________________
activation_175 (Activation)     (None, 30, 30, 128)  0           batch_normalization_175[0][0]    
__________________________________________________________________________________________________
conv2d_207 (Conv2D)             (None, 30, 30, 160)  143360      activation_175[0][0]             
__________________________________________________________________________________________________
batch_normalization_176 (BatchN (None, 30, 30, 160)  480         conv2d_207[0][0]                 
__________________________________________________________________________________________________
activation_176 (Activation)     (None, 30, 30, 160)  0           batch_normalization_176[0][0]    
__________________________________________________________________________________________________
conv2d_205 (Conv2D)             (None, 30, 30, 192)  208896      mixed_6a[0][0]                   
__________________________________________________________________________________________________
conv2d_208 (Conv2D)             (None, 30, 30, 192)  215040      activation_176[0][0]             
__________________________________________________________________________________________________
batch_normalization_174 (BatchN (None, 30, 30, 192)  576         conv2d_205[0][0]                 
__________________________________________________________________________________________________
batch_normalization_177 (BatchN (None, 30, 30, 192)  576         conv2d_208[0][0]                 
__________________________________________________________________________________________________
activation_174 (Activation)     (None, 30, 30, 192)  0           batch_normalization_174[0][0]    
__________________________________________________________________________________________________
activation_177 (Activation)     (None, 30, 30, 192)  0           batch_normalization_177[0][0]    
__________________________________________________________________________________________________
block17_1_mixed (Concatenate)   (None, 30, 30, 384)  0           activation_174[0][0]             
                                                                 activation_177[0][0]             
__________________________________________________________________________________________________
block17_1_conv (Conv2D)         (None, 30, 30, 1088) 418880      block17_1_mixed[0][0]            
__________________________________________________________________________________________________
block17_1 (Lambda)              (None, 30, 30, 1088) 0           mixed_6a[0][0]                   
                                                                 block17_1_conv[0][0]             
__________________________________________________________________________________________________
block17_1_ac (Activation)       (None, 30, 30, 1088) 0           block17_1[0][0]                  
__________________________________________________________________________________________________
conv2d_210 (Conv2D)             (None, 30, 30, 128)  139264      block17_1_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_179 (BatchN (None, 30, 30, 128)  384         conv2d_210[0][0]                 
__________________________________________________________________________________________________
activation_179 (Activation)     (None, 30, 30, 128)  0           batch_normalization_179[0][0]    
__________________________________________________________________________________________________
conv2d_211 (Conv2D)             (None, 30, 30, 160)  143360      activation_179[0][0]             
__________________________________________________________________________________________________
batch_normalization_180 (BatchN (None, 30, 30, 160)  480         conv2d_211[0][0]                 
__________________________________________________________________________________________________
activation_180 (Activation)     (None, 30, 30, 160)  0           batch_normalization_180[0][0]    
__________________________________________________________________________________________________
conv2d_209 (Conv2D)             (None, 30, 30, 192)  208896      block17_1_ac[0][0]               
__________________________________________________________________________________________________
conv2d_212 (Conv2D)             (None, 30, 30, 192)  215040      activation_180[0][0]             
__________________________________________________________________________________________________
batch_normalization_178 (BatchN (None, 30, 30, 192)  576         conv2d_209[0][0]                 
__________________________________________________________________________________________________
batch_normalization_181 (BatchN (None, 30, 30, 192)  576         conv2d_212[0][0]                 
__________________________________________________________________________________________________
activation_178 (Activation)     (None, 30, 30, 192)  0           batch_normalization_178[0][0]    
__________________________________________________________________________________________________
activation_181 (Activation)     (None, 30, 30, 192)  0           batch_normalization_181[0][0]    
__________________________________________________________________________________________________
block17_2_mixed (Concatenate)   (None, 30, 30, 384)  0           activation_178[0][0]             
                                                                 activation_181[0][0]             
__________________________________________________________________________________________________
block17_2_conv (Conv2D)         (None, 30, 30, 1088) 418880      block17_2_mixed[0][0]            
__________________________________________________________________________________________________
block17_2 (Lambda)              (None, 30, 30, 1088) 0           block17_1_ac[0][0]               
                                                                 block17_2_conv[0][0]             
__________________________________________________________________________________________________
block17_2_ac (Activation)       (None, 30, 30, 1088) 0           block17_2[0][0]                  
__________________________________________________________________________________________________
conv2d_214 (Conv2D)             (None, 30, 30, 128)  139264      block17_2_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_183 (BatchN (None, 30, 30, 128)  384         conv2d_214[0][0]                 
__________________________________________________________________________________________________
activation_183 (Activation)     (None, 30, 30, 128)  0           batch_normalization_183[0][0]    
__________________________________________________________________________________________________
conv2d_215 (Conv2D)             (None, 30, 30, 160)  143360      activation_183[0][0]             
__________________________________________________________________________________________________
batch_normalization_184 (BatchN (None, 30, 30, 160)  480         conv2d_215[0][0]                 
__________________________________________________________________________________________________
activation_184 (Activation)     (None, 30, 30, 160)  0           batch_normalization_184[0][0]    
__________________________________________________________________________________________________
conv2d_213 (Conv2D)             (None, 30, 30, 192)  208896      block17_2_ac[0][0]               
__________________________________________________________________________________________________
conv2d_216 (Conv2D)             (None, 30, 30, 192)  215040      activation_184[0][0]             
__________________________________________________________________________________________________
batch_normalization_182 (BatchN (None, 30, 30, 192)  576         conv2d_213[0][0]                 
__________________________________________________________________________________________________
batch_normalization_185 (BatchN (None, 30, 30, 192)  576         conv2d_216[0][0]                 
__________________________________________________________________________________________________
activation_182 (Activation)     (None, 30, 30, 192)  0           batch_normalization_182[0][0]    
__________________________________________________________________________________________________
activation_185 (Activation)     (None, 30, 30, 192)  0           batch_normalization_185[0][0]    
__________________________________________________________________________________________________
block17_3_mixed (Concatenate)   (None, 30, 30, 384)  0           activation_182[0][0]             
                                                                 activation_185[0][0]             
__________________________________________________________________________________________________
block17_3_conv (Conv2D)         (None, 30, 30, 1088) 418880      block17_3_mixed[0][0]            
__________________________________________________________________________________________________
block17_3 (Lambda)              (None, 30, 30, 1088) 0           block17_2_ac[0][0]               
                                                                 block17_3_conv[0][0]             
__________________________________________________________________________________________________
block17_3_ac (Activation)       (None, 30, 30, 1088) 0           block17_3[0][0]                  
__________________________________________________________________________________________________
conv2d_218 (Conv2D)             (None, 30, 30, 128)  139264      block17_3_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_187 (BatchN (None, 30, 30, 128)  384         conv2d_218[0][0]                 
__________________________________________________________________________________________________
activation_187 (Activation)     (None, 30, 30, 128)  0           batch_normalization_187[0][0]    
__________________________________________________________________________________________________
conv2d_219 (Conv2D)             (None, 30, 30, 160)  143360      activation_187[0][0]             
__________________________________________________________________________________________________
batch_normalization_188 (BatchN (None, 30, 30, 160)  480         conv2d_219[0][0]                 
__________________________________________________________________________________________________
activation_188 (Activation)     (None, 30, 30, 160)  0           batch_normalization_188[0][0]    
__________________________________________________________________________________________________
conv2d_217 (Conv2D)             (None, 30, 30, 192)  208896      block17_3_ac[0][0]               
__________________________________________________________________________________________________
conv2d_220 (Conv2D)             (None, 30, 30, 192)  215040      activation_188[0][0]             
__________________________________________________________________________________________________
batch_normalization_186 (BatchN (None, 30, 30, 192)  576         conv2d_217[0][0]                 
__________________________________________________________________________________________________
batch_normalization_189 (BatchN (None, 30, 30, 192)  576         conv2d_220[0][0]                 
__________________________________________________________________________________________________
activation_186 (Activation)     (None, 30, 30, 192)  0           batch_normalization_186[0][0]    
__________________________________________________________________________________________________
activation_189 (Activation)     (None, 30, 30, 192)  0           batch_normalization_189[0][0]    
__________________________________________________________________________________________________
block17_4_mixed (Concatenate)   (None, 30, 30, 384)  0           activation_186[0][0]             
                                                                 activation_189[0][0]             
__________________________________________________________________________________________________
block17_4_conv (Conv2D)         (None, 30, 30, 1088) 418880      block17_4_mixed[0][0]            
__________________________________________________________________________________________________
block17_4 (Lambda)              (None, 30, 30, 1088) 0           block17_3_ac[0][0]               
                                                                 block17_4_conv[0][0]             
__________________________________________________________________________________________________
block17_4_ac (Activation)       (None, 30, 30, 1088) 0           block17_4[0][0]                  
__________________________________________________________________________________________________
conv2d_222 (Conv2D)             (None, 30, 30, 128)  139264      block17_4_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_191 (BatchN (None, 30, 30, 128)  384         conv2d_222[0][0]                 
__________________________________________________________________________________________________
activation_191 (Activation)     (None, 30, 30, 128)  0           batch_normalization_191[0][0]    
__________________________________________________________________________________________________
conv2d_223 (Conv2D)             (None, 30, 30, 160)  143360      activation_191[0][0]             
__________________________________________________________________________________________________
batch_normalization_192 (BatchN (None, 30, 30, 160)  480         conv2d_223[0][0]                 
__________________________________________________________________________________________________
activation_192 (Activation)     (None, 30, 30, 160)  0           batch_normalization_192[0][0]    
__________________________________________________________________________________________________
conv2d_221 (Conv2D)             (None, 30, 30, 192)  208896      block17_4_ac[0][0]               
__________________________________________________________________________________________________
conv2d_224 (Conv2D)             (None, 30, 30, 192)  215040      activation_192[0][0]             
__________________________________________________________________________________________________
batch_normalization_190 (BatchN (None, 30, 30, 192)  576         conv2d_221[0][0]                 
__________________________________________________________________________________________________
batch_normalization_193 (BatchN (None, 30, 30, 192)  576         conv2d_224[0][0]                 
__________________________________________________________________________________________________
activation_190 (Activation)     (None, 30, 30, 192)  0           batch_normalization_190[0][0]    
__________________________________________________________________________________________________
activation_193 (Activation)     (None, 30, 30, 192)  0           batch_normalization_193[0][0]    
__________________________________________________________________________________________________
block17_5_mixed (Concatenate)   (None, 30, 30, 384)  0           activation_190[0][0]             
                                                                 activation_193[0][0]             
__________________________________________________________________________________________________
block17_5_conv (Conv2D)         (None, 30, 30, 1088) 418880      block17_5_mixed[0][0]            
__________________________________________________________________________________________________
block17_5 (Lambda)              (None, 30, 30, 1088) 0           block17_4_ac[0][0]               
                                                                 block17_5_conv[0][0]             
__________________________________________________________________________________________________
block17_5_ac (Activation)       (None, 30, 30, 1088) 0           block17_5[0][0]                  
__________________________________________________________________________________________________
conv2d_226 (Conv2D)             (None, 30, 30, 128)  139264      block17_5_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_195 (BatchN (None, 30, 30, 128)  384         conv2d_226[0][0]                 
__________________________________________________________________________________________________
activation_195 (Activation)     (None, 30, 30, 128)  0           batch_normalization_195[0][0]    
__________________________________________________________________________________________________
conv2d_227 (Conv2D)             (None, 30, 30, 160)  143360      activation_195[0][0]             
__________________________________________________________________________________________________
batch_normalization_196 (BatchN (None, 30, 30, 160)  480         conv2d_227[0][0]                 
__________________________________________________________________________________________________
activation_196 (Activation)     (None, 30, 30, 160)  0           batch_normalization_196[0][0]    
__________________________________________________________________________________________________
conv2d_225 (Conv2D)             (None, 30, 30, 192)  208896      block17_5_ac[0][0]               
__________________________________________________________________________________________________
conv2d_228 (Conv2D)             (None, 30, 30, 192)  215040      activation_196[0][0]             
__________________________________________________________________________________________________
batch_normalization_194 (BatchN (None, 30, 30, 192)  576         conv2d_225[0][0]                 
__________________________________________________________________________________________________
batch_normalization_197 (BatchN (None, 30, 30, 192)  576         conv2d_228[0][0]                 
__________________________________________________________________________________________________
activation_194 (Activation)     (None, 30, 30, 192)  0           batch_normalization_194[0][0]    
__________________________________________________________________________________________________
activation_197 (Activation)     (None, 30, 30, 192)  0           batch_normalization_197[0][0]    
__________________________________________________________________________________________________
block17_6_mixed (Concatenate)   (None, 30, 30, 384)  0           activation_194[0][0]             
                                                                 activation_197[0][0]             
__________________________________________________________________________________________________
block17_6_conv (Conv2D)         (None, 30, 30, 1088) 418880      block17_6_mixed[0][0]            
__________________________________________________________________________________________________
block17_6 (Lambda)              (None, 30, 30, 1088) 0           block17_5_ac[0][0]               
                                                                 block17_6_conv[0][0]             
__________________________________________________________________________________________________
block17_6_ac (Activation)       (None, 30, 30, 1088) 0           block17_6[0][0]                  
__________________________________________________________________________________________________
conv2d_230 (Conv2D)             (None, 30, 30, 128)  139264      block17_6_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_199 (BatchN (None, 30, 30, 128)  384         conv2d_230[0][0]                 
__________________________________________________________________________________________________
activation_199 (Activation)     (None, 30, 30, 128)  0           batch_normalization_199[0][0]    
__________________________________________________________________________________________________
conv2d_231 (Conv2D)             (None, 30, 30, 160)  143360      activation_199[0][0]             
__________________________________________________________________________________________________
batch_normalization_200 (BatchN (None, 30, 30, 160)  480         conv2d_231[0][0]                 
__________________________________________________________________________________________________
activation_200 (Activation)     (None, 30, 30, 160)  0           batch_normalization_200[0][0]    
__________________________________________________________________________________________________
conv2d_229 (Conv2D)             (None, 30, 30, 192)  208896      block17_6_ac[0][0]               
__________________________________________________________________________________________________
conv2d_232 (Conv2D)             (None, 30, 30, 192)  215040      activation_200[0][0]             
__________________________________________________________________________________________________
batch_normalization_198 (BatchN (None, 30, 30, 192)  576         conv2d_229[0][0]                 
__________________________________________________________________________________________________
batch_normalization_201 (BatchN (None, 30, 30, 192)  576         conv2d_232[0][0]                 
__________________________________________________________________________________________________
activation_198 (Activation)     (None, 30, 30, 192)  0           batch_normalization_198[0][0]    
__________________________________________________________________________________________________
activation_201 (Activation)     (None, 30, 30, 192)  0           batch_normalization_201[0][0]    
__________________________________________________________________________________________________
block17_7_mixed (Concatenate)   (None, 30, 30, 384)  0           activation_198[0][0]             
                                                                 activation_201[0][0]             
__________________________________________________________________________________________________
block17_7_conv (Conv2D)         (None, 30, 30, 1088) 418880      block17_7_mixed[0][0]            
__________________________________________________________________________________________________
block17_7 (Lambda)              (None, 30, 30, 1088) 0           block17_6_ac[0][0]               
                                                                 block17_7_conv[0][0]             
__________________________________________________________________________________________________
block17_7_ac (Activation)       (None, 30, 30, 1088) 0           block17_7[0][0]                  
__________________________________________________________________________________________________
conv2d_234 (Conv2D)             (None, 30, 30, 128)  139264      block17_7_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_203 (BatchN (None, 30, 30, 128)  384         conv2d_234[0][0]                 
__________________________________________________________________________________________________
activation_203 (Activation)     (None, 30, 30, 128)  0           batch_normalization_203[0][0]    
__________________________________________________________________________________________________
conv2d_235 (Conv2D)             (None, 30, 30, 160)  143360      activation_203[0][0]             
__________________________________________________________________________________________________
batch_normalization_204 (BatchN (None, 30, 30, 160)  480         conv2d_235[0][0]                 
__________________________________________________________________________________________________
activation_204 (Activation)     (None, 30, 30, 160)  0           batch_normalization_204[0][0]    
__________________________________________________________________________________________________
conv2d_233 (Conv2D)             (None, 30, 30, 192)  208896      block17_7_ac[0][0]               
__________________________________________________________________________________________________
conv2d_236 (Conv2D)             (None, 30, 30, 192)  215040      activation_204[0][0]             
__________________________________________________________________________________________________
batch_normalization_202 (BatchN (None, 30, 30, 192)  576         conv2d_233[0][0]                 
__________________________________________________________________________________________________
batch_normalization_205 (BatchN (None, 30, 30, 192)  576         conv2d_236[0][0]                 
__________________________________________________________________________________________________
activation_202 (Activation)     (None, 30, 30, 192)  0           batch_normalization_202[0][0]    
__________________________________________________________________________________________________
activation_205 (Activation)     (None, 30, 30, 192)  0           batch_normalization_205[0][0]    
__________________________________________________________________________________________________
block17_8_mixed (Concatenate)   (None, 30, 30, 384)  0           activation_202[0][0]             
                                                                 activation_205[0][0]             
__________________________________________________________________________________________________
block17_8_conv (Conv2D)         (None, 30, 30, 1088) 418880      block17_8_mixed[0][0]            
__________________________________________________________________________________________________
block17_8 (Lambda)              (None, 30, 30, 1088) 0           block17_7_ac[0][0]               
                                                                 block17_8_conv[0][0]             
__________________________________________________________________________________________________
block17_8_ac (Activation)       (None, 30, 30, 1088) 0           block17_8[0][0]                  
__________________________________________________________________________________________________
conv2d_238 (Conv2D)             (None, 30, 30, 128)  139264      block17_8_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_207 (BatchN (None, 30, 30, 128)  384         conv2d_238[0][0]                 
__________________________________________________________________________________________________
activation_207 (Activation)     (None, 30, 30, 128)  0           batch_normalization_207[0][0]    
__________________________________________________________________________________________________
conv2d_239 (Conv2D)             (None, 30, 30, 160)  143360      activation_207[0][0]             
__________________________________________________________________________________________________
batch_normalization_208 (BatchN (None, 30, 30, 160)  480         conv2d_239[0][0]                 
__________________________________________________________________________________________________
activation_208 (Activation)     (None, 30, 30, 160)  0           batch_normalization_208[0][0]    
__________________________________________________________________________________________________
conv2d_237 (Conv2D)             (None, 30, 30, 192)  208896      block17_8_ac[0][0]               
__________________________________________________________________________________________________
conv2d_240 (Conv2D)             (None, 30, 30, 192)  215040      activation_208[0][0]             
__________________________________________________________________________________________________
batch_normalization_206 (BatchN (None, 30, 30, 192)  576         conv2d_237[0][0]                 
__________________________________________________________________________________________________
batch_normalization_209 (BatchN (None, 30, 30, 192)  576         conv2d_240[0][0]                 
__________________________________________________________________________________________________
activation_206 (Activation)     (None, 30, 30, 192)  0           batch_normalization_206[0][0]    
__________________________________________________________________________________________________
activation_209 (Activation)     (None, 30, 30, 192)  0           batch_normalization_209[0][0]    
__________________________________________________________________________________________________
block17_9_mixed (Concatenate)   (None, 30, 30, 384)  0           activation_206[0][0]             
                                                                 activation_209[0][0]             
__________________________________________________________________________________________________
block17_9_conv (Conv2D)         (None, 30, 30, 1088) 418880      block17_9_mixed[0][0]            
__________________________________________________________________________________________________
block17_9 (Lambda)              (None, 30, 30, 1088) 0           block17_8_ac[0][0]               
                                                                 block17_9_conv[0][0]             
__________________________________________________________________________________________________
block17_9_ac (Activation)       (None, 30, 30, 1088) 0           block17_9[0][0]                  
__________________________________________________________________________________________________
conv2d_242 (Conv2D)             (None, 30, 30, 128)  139264      block17_9_ac[0][0]               
__________________________________________________________________________________________________
batch_normalization_211 (BatchN (None, 30, 30, 128)  384         conv2d_242[0][0]                 
__________________________________________________________________________________________________
activation_211 (Activation)     (None, 30, 30, 128)  0           batch_normalization_211[0][0]    
__________________________________________________________________________________________________
conv2d_243 (Conv2D)             (None, 30, 30, 160)  143360      activation_211[0][0]             
__________________________________________________________________________________________________
batch_normalization_212 (BatchN (None, 30, 30, 160)  480         conv2d_243[0][0]                 
__________________________________________________________________________________________________
activation_212 (Activation)     (None, 30, 30, 160)  0           batch_normalization_212[0][0]    
__________________________________________________________________________________________________
conv2d_241 (Conv2D)             (None, 30, 30, 192)  208896      block17_9_ac[0][0]               
__________________________________________________________________________________________________
conv2d_244 (Conv2D)             (None, 30, 30, 192)  215040      activation_212[0][0]             
__________________________________________________________________________________________________
batch_normalization_210 (BatchN (None, 30, 30, 192)  576         conv2d_241[0][0]                 
__________________________________________________________________________________________________
batch_normalization_213 (BatchN (None, 30, 30, 192)  576         conv2d_244[0][0]                 
__________________________________________________________________________________________________
activation_210 (Activation)     (None, 30, 30, 192)  0           batch_normalization_210[0][0]    
__________________________________________________________________________________________________
activation_213 (Activation)     (None, 30, 30, 192)  0           batch_normalization_213[0][0]    
__________________________________________________________________________________________________
block17_10_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_210[0][0]             
                                                                 activation_213[0][0]             
__________________________________________________________________________________________________
block17_10_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_10_mixed[0][0]           
__________________________________________________________________________________________________
block17_10 (Lambda)             (None, 30, 30, 1088) 0           block17_9_ac[0][0]               
                                                                 block17_10_conv[0][0]            
__________________________________________________________________________________________________
block17_10_ac (Activation)      (None, 30, 30, 1088) 0           block17_10[0][0]                 
__________________________________________________________________________________________________
conv2d_246 (Conv2D)             (None, 30, 30, 128)  139264      block17_10_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_215 (BatchN (None, 30, 30, 128)  384         conv2d_246[0][0]                 
__________________________________________________________________________________________________
activation_215 (Activation)     (None, 30, 30, 128)  0           batch_normalization_215[0][0]    
__________________________________________________________________________________________________
conv2d_247 (Conv2D)             (None, 30, 30, 160)  143360      activation_215[0][0]             
__________________________________________________________________________________________________
batch_normalization_216 (BatchN (None, 30, 30, 160)  480         conv2d_247[0][0]                 
__________________________________________________________________________________________________
activation_216 (Activation)     (None, 30, 30, 160)  0           batch_normalization_216[0][0]    
__________________________________________________________________________________________________
conv2d_245 (Conv2D)             (None, 30, 30, 192)  208896      block17_10_ac[0][0]              
__________________________________________________________________________________________________
conv2d_248 (Conv2D)             (None, 30, 30, 192)  215040      activation_216[0][0]             
__________________________________________________________________________________________________
batch_normalization_214 (BatchN (None, 30, 30, 192)  576         conv2d_245[0][0]                 
__________________________________________________________________________________________________
batch_normalization_217 (BatchN (None, 30, 30, 192)  576         conv2d_248[0][0]                 
__________________________________________________________________________________________________
activation_214 (Activation)     (None, 30, 30, 192)  0           batch_normalization_214[0][0]    
__________________________________________________________________________________________________
activation_217 (Activation)     (None, 30, 30, 192)  0           batch_normalization_217[0][0]    
__________________________________________________________________________________________________
block17_11_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_214[0][0]             
                                                                 activation_217[0][0]             
__________________________________________________________________________________________________
block17_11_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_11_mixed[0][0]           
__________________________________________________________________________________________________
block17_11 (Lambda)             (None, 30, 30, 1088) 0           block17_10_ac[0][0]              
                                                                 block17_11_conv[0][0]            
__________________________________________________________________________________________________
block17_11_ac (Activation)      (None, 30, 30, 1088) 0           block17_11[0][0]                 
__________________________________________________________________________________________________
conv2d_250 (Conv2D)             (None, 30, 30, 128)  139264      block17_11_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_219 (BatchN (None, 30, 30, 128)  384         conv2d_250[0][0]                 
__________________________________________________________________________________________________
activation_219 (Activation)     (None, 30, 30, 128)  0           batch_normalization_219[0][0]    
__________________________________________________________________________________________________
conv2d_251 (Conv2D)             (None, 30, 30, 160)  143360      activation_219[0][0]             
__________________________________________________________________________________________________
batch_normalization_220 (BatchN (None, 30, 30, 160)  480         conv2d_251[0][0]                 
__________________________________________________________________________________________________
activation_220 (Activation)     (None, 30, 30, 160)  0           batch_normalization_220[0][0]    
__________________________________________________________________________________________________
conv2d_249 (Conv2D)             (None, 30, 30, 192)  208896      block17_11_ac[0][0]              
__________________________________________________________________________________________________
conv2d_252 (Conv2D)             (None, 30, 30, 192)  215040      activation_220[0][0]             
__________________________________________________________________________________________________
batch_normalization_218 (BatchN (None, 30, 30, 192)  576         conv2d_249[0][0]                 
__________________________________________________________________________________________________
batch_normalization_221 (BatchN (None, 30, 30, 192)  576         conv2d_252[0][0]                 
__________________________________________________________________________________________________
activation_218 (Activation)     (None, 30, 30, 192)  0           batch_normalization_218[0][0]    
__________________________________________________________________________________________________
activation_221 (Activation)     (None, 30, 30, 192)  0           batch_normalization_221[0][0]    
__________________________________________________________________________________________________
block17_12_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_218[0][0]             
                                                                 activation_221[0][0]             
__________________________________________________________________________________________________
block17_12_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_12_mixed[0][0]           
__________________________________________________________________________________________________
block17_12 (Lambda)             (None, 30, 30, 1088) 0           block17_11_ac[0][0]              
                                                                 block17_12_conv[0][0]            
__________________________________________________________________________________________________
block17_12_ac (Activation)      (None, 30, 30, 1088) 0           block17_12[0][0]                 
__________________________________________________________________________________________________
conv2d_254 (Conv2D)             (None, 30, 30, 128)  139264      block17_12_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_223 (BatchN (None, 30, 30, 128)  384         conv2d_254[0][0]                 
__________________________________________________________________________________________________
activation_223 (Activation)     (None, 30, 30, 128)  0           batch_normalization_223[0][0]    
__________________________________________________________________________________________________
conv2d_255 (Conv2D)             (None, 30, 30, 160)  143360      activation_223[0][0]             
__________________________________________________________________________________________________
batch_normalization_224 (BatchN (None, 30, 30, 160)  480         conv2d_255[0][0]                 
__________________________________________________________________________________________________
activation_224 (Activation)     (None, 30, 30, 160)  0           batch_normalization_224[0][0]    
__________________________________________________________________________________________________
conv2d_253 (Conv2D)             (None, 30, 30, 192)  208896      block17_12_ac[0][0]              
__________________________________________________________________________________________________
conv2d_256 (Conv2D)             (None, 30, 30, 192)  215040      activation_224[0][0]             
__________________________________________________________________________________________________
batch_normalization_222 (BatchN (None, 30, 30, 192)  576         conv2d_253[0][0]                 
__________________________________________________________________________________________________
batch_normalization_225 (BatchN (None, 30, 30, 192)  576         conv2d_256[0][0]                 
__________________________________________________________________________________________________
activation_222 (Activation)     (None, 30, 30, 192)  0           batch_normalization_222[0][0]    
__________________________________________________________________________________________________
activation_225 (Activation)     (None, 30, 30, 192)  0           batch_normalization_225[0][0]    
__________________________________________________________________________________________________
block17_13_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_222[0][0]             
                                                                 activation_225[0][0]             
__________________________________________________________________________________________________
block17_13_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_13_mixed[0][0]           
__________________________________________________________________________________________________
block17_13 (Lambda)             (None, 30, 30, 1088) 0           block17_12_ac[0][0]              
                                                                 block17_13_conv[0][0]            
__________________________________________________________________________________________________
block17_13_ac (Activation)      (None, 30, 30, 1088) 0           block17_13[0][0]                 
__________________________________________________________________________________________________
conv2d_258 (Conv2D)             (None, 30, 30, 128)  139264      block17_13_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_227 (BatchN (None, 30, 30, 128)  384         conv2d_258[0][0]                 
__________________________________________________________________________________________________
activation_227 (Activation)     (None, 30, 30, 128)  0           batch_normalization_227[0][0]    
__________________________________________________________________________________________________
conv2d_259 (Conv2D)             (None, 30, 30, 160)  143360      activation_227[0][0]             
__________________________________________________________________________________________________
batch_normalization_228 (BatchN (None, 30, 30, 160)  480         conv2d_259[0][0]                 
__________________________________________________________________________________________________
activation_228 (Activation)     (None, 30, 30, 160)  0           batch_normalization_228[0][0]    
__________________________________________________________________________________________________
conv2d_257 (Conv2D)             (None, 30, 30, 192)  208896      block17_13_ac[0][0]              
__________________________________________________________________________________________________
conv2d_260 (Conv2D)             (None, 30, 30, 192)  215040      activation_228[0][0]             
__________________________________________________________________________________________________
batch_normalization_226 (BatchN (None, 30, 30, 192)  576         conv2d_257[0][0]                 
__________________________________________________________________________________________________
batch_normalization_229 (BatchN (None, 30, 30, 192)  576         conv2d_260[0][0]                 
__________________________________________________________________________________________________
activation_226 (Activation)     (None, 30, 30, 192)  0           batch_normalization_226[0][0]    
__________________________________________________________________________________________________
activation_229 (Activation)     (None, 30, 30, 192)  0           batch_normalization_229[0][0]    
__________________________________________________________________________________________________
block17_14_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_226[0][0]             
                                                                 activation_229[0][0]             
__________________________________________________________________________________________________
block17_14_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_14_mixed[0][0]           
__________________________________________________________________________________________________
block17_14 (Lambda)             (None, 30, 30, 1088) 0           block17_13_ac[0][0]              
                                                                 block17_14_conv[0][0]            
__________________________________________________________________________________________________
block17_14_ac (Activation)      (None, 30, 30, 1088) 0           block17_14[0][0]                 
__________________________________________________________________________________________________
conv2d_262 (Conv2D)             (None, 30, 30, 128)  139264      block17_14_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_231 (BatchN (None, 30, 30, 128)  384         conv2d_262[0][0]                 
__________________________________________________________________________________________________
activation_231 (Activation)     (None, 30, 30, 128)  0           batch_normalization_231[0][0]    
__________________________________________________________________________________________________
conv2d_263 (Conv2D)             (None, 30, 30, 160)  143360      activation_231[0][0]             
__________________________________________________________________________________________________
batch_normalization_232 (BatchN (None, 30, 30, 160)  480         conv2d_263[0][0]                 
__________________________________________________________________________________________________
activation_232 (Activation)     (None, 30, 30, 160)  0           batch_normalization_232[0][0]    
__________________________________________________________________________________________________
conv2d_261 (Conv2D)             (None, 30, 30, 192)  208896      block17_14_ac[0][0]              
__________________________________________________________________________________________________
conv2d_264 (Conv2D)             (None, 30, 30, 192)  215040      activation_232[0][0]             
__________________________________________________________________________________________________
batch_normalization_230 (BatchN (None, 30, 30, 192)  576         conv2d_261[0][0]                 
__________________________________________________________________________________________________
batch_normalization_233 (BatchN (None, 30, 30, 192)  576         conv2d_264[0][0]                 
__________________________________________________________________________________________________
activation_230 (Activation)     (None, 30, 30, 192)  0           batch_normalization_230[0][0]    
__________________________________________________________________________________________________
activation_233 (Activation)     (None, 30, 30, 192)  0           batch_normalization_233[0][0]    
__________________________________________________________________________________________________
block17_15_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_230[0][0]             
                                                                 activation_233[0][0]             
__________________________________________________________________________________________________
block17_15_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_15_mixed[0][0]           
__________________________________________________________________________________________________
block17_15 (Lambda)             (None, 30, 30, 1088) 0           block17_14_ac[0][0]              
                                                                 block17_15_conv[0][0]            
__________________________________________________________________________________________________
block17_15_ac (Activation)      (None, 30, 30, 1088) 0           block17_15[0][0]                 
__________________________________________________________________________________________________
conv2d_266 (Conv2D)             (None, 30, 30, 128)  139264      block17_15_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_235 (BatchN (None, 30, 30, 128)  384         conv2d_266[0][0]                 
__________________________________________________________________________________________________
activation_235 (Activation)     (None, 30, 30, 128)  0           batch_normalization_235[0][0]    
__________________________________________________________________________________________________
conv2d_267 (Conv2D)             (None, 30, 30, 160)  143360      activation_235[0][0]             
__________________________________________________________________________________________________
batch_normalization_236 (BatchN (None, 30, 30, 160)  480         conv2d_267[0][0]                 
__________________________________________________________________________________________________
activation_236 (Activation)     (None, 30, 30, 160)  0           batch_normalization_236[0][0]    
__________________________________________________________________________________________________
conv2d_265 (Conv2D)             (None, 30, 30, 192)  208896      block17_15_ac[0][0]              
__________________________________________________________________________________________________
conv2d_268 (Conv2D)             (None, 30, 30, 192)  215040      activation_236[0][0]             
__________________________________________________________________________________________________
batch_normalization_234 (BatchN (None, 30, 30, 192)  576         conv2d_265[0][0]                 
__________________________________________________________________________________________________
batch_normalization_237 (BatchN (None, 30, 30, 192)  576         conv2d_268[0][0]                 
__________________________________________________________________________________________________
activation_234 (Activation)     (None, 30, 30, 192)  0           batch_normalization_234[0][0]    
__________________________________________________________________________________________________
activation_237 (Activation)     (None, 30, 30, 192)  0           batch_normalization_237[0][0]    
__________________________________________________________________________________________________
block17_16_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_234[0][0]             
                                                                 activation_237[0][0]             
__________________________________________________________________________________________________
block17_16_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_16_mixed[0][0]           
__________________________________________________________________________________________________
block17_16 (Lambda)             (None, 30, 30, 1088) 0           block17_15_ac[0][0]              
                                                                 block17_16_conv[0][0]            
__________________________________________________________________________________________________
block17_16_ac (Activation)      (None, 30, 30, 1088) 0           block17_16[0][0]                 
__________________________________________________________________________________________________
conv2d_270 (Conv2D)             (None, 30, 30, 128)  139264      block17_16_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_239 (BatchN (None, 30, 30, 128)  384         conv2d_270[0][0]                 
__________________________________________________________________________________________________
activation_239 (Activation)     (None, 30, 30, 128)  0           batch_normalization_239[0][0]    
__________________________________________________________________________________________________
conv2d_271 (Conv2D)             (None, 30, 30, 160)  143360      activation_239[0][0]             
__________________________________________________________________________________________________
batch_normalization_240 (BatchN (None, 30, 30, 160)  480         conv2d_271[0][0]                 
__________________________________________________________________________________________________
activation_240 (Activation)     (None, 30, 30, 160)  0           batch_normalization_240[0][0]    
__________________________________________________________________________________________________
conv2d_269 (Conv2D)             (None, 30, 30, 192)  208896      block17_16_ac[0][0]              
__________________________________________________________________________________________________
conv2d_272 (Conv2D)             (None, 30, 30, 192)  215040      activation_240[0][0]             
__________________________________________________________________________________________________
batch_normalization_238 (BatchN (None, 30, 30, 192)  576         conv2d_269[0][0]                 
__________________________________________________________________________________________________
batch_normalization_241 (BatchN (None, 30, 30, 192)  576         conv2d_272[0][0]                 
__________________________________________________________________________________________________
activation_238 (Activation)     (None, 30, 30, 192)  0           batch_normalization_238[0][0]    
__________________________________________________________________________________________________
activation_241 (Activation)     (None, 30, 30, 192)  0           batch_normalization_241[0][0]    
__________________________________________________________________________________________________
block17_17_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_238[0][0]             
                                                                 activation_241[0][0]             
__________________________________________________________________________________________________
block17_17_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_17_mixed[0][0]           
__________________________________________________________________________________________________
block17_17 (Lambda)             (None, 30, 30, 1088) 0           block17_16_ac[0][0]              
                                                                 block17_17_conv[0][0]            
__________________________________________________________________________________________________
block17_17_ac (Activation)      (None, 30, 30, 1088) 0           block17_17[0][0]                 
__________________________________________________________________________________________________
conv2d_274 (Conv2D)             (None, 30, 30, 128)  139264      block17_17_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_243 (BatchN (None, 30, 30, 128)  384         conv2d_274[0][0]                 
__________________________________________________________________________________________________
activation_243 (Activation)     (None, 30, 30, 128)  0           batch_normalization_243[0][0]    
__________________________________________________________________________________________________
conv2d_275 (Conv2D)             (None, 30, 30, 160)  143360      activation_243[0][0]             
__________________________________________________________________________________________________
batch_normalization_244 (BatchN (None, 30, 30, 160)  480         conv2d_275[0][0]                 
__________________________________________________________________________________________________
activation_244 (Activation)     (None, 30, 30, 160)  0           batch_normalization_244[0][0]    
__________________________________________________________________________________________________
conv2d_273 (Conv2D)             (None, 30, 30, 192)  208896      block17_17_ac[0][0]              
__________________________________________________________________________________________________
conv2d_276 (Conv2D)             (None, 30, 30, 192)  215040      activation_244[0][0]             
__________________________________________________________________________________________________
batch_normalization_242 (BatchN (None, 30, 30, 192)  576         conv2d_273[0][0]                 
__________________________________________________________________________________________________
batch_normalization_245 (BatchN (None, 30, 30, 192)  576         conv2d_276[0][0]                 
__________________________________________________________________________________________________
activation_242 (Activation)     (None, 30, 30, 192)  0           batch_normalization_242[0][0]    
__________________________________________________________________________________________________
activation_245 (Activation)     (None, 30, 30, 192)  0           batch_normalization_245[0][0]    
__________________________________________________________________________________________________
block17_18_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_242[0][0]             
                                                                 activation_245[0][0]             
__________________________________________________________________________________________________
block17_18_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_18_mixed[0][0]           
__________________________________________________________________________________________________
block17_18 (Lambda)             (None, 30, 30, 1088) 0           block17_17_ac[0][0]              
                                                                 block17_18_conv[0][0]            
__________________________________________________________________________________________________
block17_18_ac (Activation)      (None, 30, 30, 1088) 0           block17_18[0][0]                 
__________________________________________________________________________________________________
conv2d_278 (Conv2D)             (None, 30, 30, 128)  139264      block17_18_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_247 (BatchN (None, 30, 30, 128)  384         conv2d_278[0][0]                 
__________________________________________________________________________________________________
activation_247 (Activation)     (None, 30, 30, 128)  0           batch_normalization_247[0][0]    
__________________________________________________________________________________________________
conv2d_279 (Conv2D)             (None, 30, 30, 160)  143360      activation_247[0][0]             
__________________________________________________________________________________________________
batch_normalization_248 (BatchN (None, 30, 30, 160)  480         conv2d_279[0][0]                 
__________________________________________________________________________________________________
activation_248 (Activation)     (None, 30, 30, 160)  0           batch_normalization_248[0][0]    
__________________________________________________________________________________________________
conv2d_277 (Conv2D)             (None, 30, 30, 192)  208896      block17_18_ac[0][0]              
__________________________________________________________________________________________________
conv2d_280 (Conv2D)             (None, 30, 30, 192)  215040      activation_248[0][0]             
__________________________________________________________________________________________________
batch_normalization_246 (BatchN (None, 30, 30, 192)  576         conv2d_277[0][0]                 
__________________________________________________________________________________________________
batch_normalization_249 (BatchN (None, 30, 30, 192)  576         conv2d_280[0][0]                 
__________________________________________________________________________________________________
activation_246 (Activation)     (None, 30, 30, 192)  0           batch_normalization_246[0][0]    
__________________________________________________________________________________________________
activation_249 (Activation)     (None, 30, 30, 192)  0           batch_normalization_249[0][0]    
__________________________________________________________________________________________________
block17_19_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_246[0][0]             
                                                                 activation_249[0][0]             
__________________________________________________________________________________________________
block17_19_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_19_mixed[0][0]           
__________________________________________________________________________________________________
block17_19 (Lambda)             (None, 30, 30, 1088) 0           block17_18_ac[0][0]              
                                                                 block17_19_conv[0][0]            
__________________________________________________________________________________________________
block17_19_ac (Activation)      (None, 30, 30, 1088) 0           block17_19[0][0]                 
__________________________________________________________________________________________________
conv2d_282 (Conv2D)             (None, 30, 30, 128)  139264      block17_19_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_251 (BatchN (None, 30, 30, 128)  384         conv2d_282[0][0]                 
__________________________________________________________________________________________________
activation_251 (Activation)     (None, 30, 30, 128)  0           batch_normalization_251[0][0]    
__________________________________________________________________________________________________
conv2d_283 (Conv2D)             (None, 30, 30, 160)  143360      activation_251[0][0]             
__________________________________________________________________________________________________
batch_normalization_252 (BatchN (None, 30, 30, 160)  480         conv2d_283[0][0]                 
__________________________________________________________________________________________________
activation_252 (Activation)     (None, 30, 30, 160)  0           batch_normalization_252[0][0]    
__________________________________________________________________________________________________
conv2d_281 (Conv2D)             (None, 30, 30, 192)  208896      block17_19_ac[0][0]              
__________________________________________________________________________________________________
conv2d_284 (Conv2D)             (None, 30, 30, 192)  215040      activation_252[0][0]             
__________________________________________________________________________________________________
batch_normalization_250 (BatchN (None, 30, 30, 192)  576         conv2d_281[0][0]                 
__________________________________________________________________________________________________
batch_normalization_253 (BatchN (None, 30, 30, 192)  576         conv2d_284[0][0]                 
__________________________________________________________________________________________________
activation_250 (Activation)     (None, 30, 30, 192)  0           batch_normalization_250[0][0]    
__________________________________________________________________________________________________
activation_253 (Activation)     (None, 30, 30, 192)  0           batch_normalization_253[0][0]    
__________________________________________________________________________________________________
block17_20_mixed (Concatenate)  (None, 30, 30, 384)  0           activation_250[0][0]             
                                                                 activation_253[0][0]             
__________________________________________________________________________________________________
block17_20_conv (Conv2D)        (None, 30, 30, 1088) 418880      block17_20_mixed[0][0]           
__________________________________________________________________________________________________
block17_20 (Lambda)             (None, 30, 30, 1088) 0           block17_19_ac[0][0]              
                                                                 block17_20_conv[0][0]            
__________________________________________________________________________________________________
block17_20_ac (Activation)      (None, 30, 30, 1088) 0           block17_20[0][0]                 
__________________________________________________________________________________________________
conv2d_289 (Conv2D)             (None, 30, 30, 256)  278528      block17_20_ac[0][0]              
__________________________________________________________________________________________________
batch_normalization_258 (BatchN (None, 30, 30, 256)  768         conv2d_289[0][0]                 
__________________________________________________________________________________________________
activation_258 (Activation)     (None, 30, 30, 256)  0           batch_normalization_258[0][0]    
__________________________________________________________________________________________________
conv2d_285 (Conv2D)             (None, 30, 30, 256)  278528      block17_20_ac[0][0]              
__________________________________________________________________________________________________
conv2d_287 (Conv2D)             (None, 30, 30, 256)  278528      block17_20_ac[0][0]              
__________________________________________________________________________________________________
conv2d_290 (Conv2D)             (None, 30, 30, 288)  663552      activation_258[0][0]             
__________________________________________________________________________________________________
batch_normalization_254 (BatchN (None, 30, 30, 256)  768         conv2d_285[0][0]                 
__________________________________________________________________________________________________
batch_normalization_256 (BatchN (None, 30, 30, 256)  768         conv2d_287[0][0]                 
__________________________________________________________________________________________________
batch_normalization_259 (BatchN (None, 30, 30, 288)  864         conv2d_290[0][0]                 
__________________________________________________________________________________________________
activation_254 (Activation)     (None, 30, 30, 256)  0           batch_normalization_254[0][0]    
__________________________________________________________________________________________________
activation_256 (Activation)     (None, 30, 30, 256)  0           batch_normalization_256[0][0]    
__________________________________________________________________________________________________
activation_259 (Activation)     (None, 30, 30, 288)  0           batch_normalization_259[0][0]    
__________________________________________________________________________________________________
conv2d_286 (Conv2D)             (None, 14, 14, 384)  884736      activation_254[0][0]             
__________________________________________________________________________________________________
conv2d_288 (Conv2D)             (None, 14, 14, 288)  663552      activation_256[0][0]             
__________________________________________________________________________________________________
conv2d_291 (Conv2D)             (None, 14, 14, 320)  829440      activation_259[0][0]             
__________________________________________________________________________________________________
batch_normalization_255 (BatchN (None, 14, 14, 384)  1152        conv2d_286[0][0]                 
__________________________________________________________________________________________________
batch_normalization_257 (BatchN (None, 14, 14, 288)  864         conv2d_288[0][0]                 
__________________________________________________________________________________________________
batch_normalization_260 (BatchN (None, 14, 14, 320)  960         conv2d_291[0][0]                 
__________________________________________________________________________________________________
activation_255 (Activation)     (None, 14, 14, 384)  0           batch_normalization_255[0][0]    
__________________________________________________________________________________________________
activation_257 (Activation)     (None, 14, 14, 288)  0           batch_normalization_257[0][0]    
__________________________________________________________________________________________________
activation_260 (Activation)     (None, 14, 14, 320)  0           batch_normalization_260[0][0]    
__________________________________________________________________________________________________
max_pooling2d_17 (MaxPooling2D) (None, 14, 14, 1088) 0           block17_20_ac[0][0]              
__________________________________________________________________________________________________
mixed_7a (Concatenate)          (None, 14, 14, 2080) 0           activation_255[0][0]             
                                                                 activation_257[0][0]             
                                                                 activation_260[0][0]             
                                                                 max_pooling2d_17[0][0]           
__________________________________________________________________________________________________
conv2d_293 (Conv2D)             (None, 14, 14, 192)  399360      mixed_7a[0][0]                   
__________________________________________________________________________________________________
batch_normalization_262 (BatchN (None, 14, 14, 192)  576         conv2d_293[0][0]                 
__________________________________________________________________________________________________
activation_262 (Activation)     (None, 14, 14, 192)  0           batch_normalization_262[0][0]    
__________________________________________________________________________________________________
conv2d_294 (Conv2D)             (None, 14, 14, 224)  129024      activation_262[0][0]             
__________________________________________________________________________________________________
batch_normalization_263 (BatchN (None, 14, 14, 224)  672         conv2d_294[0][0]                 
__________________________________________________________________________________________________
activation_263 (Activation)     (None, 14, 14, 224)  0           batch_normalization_263[0][0]    
__________________________________________________________________________________________________
conv2d_292 (Conv2D)             (None, 14, 14, 192)  399360      mixed_7a[0][0]                   
__________________________________________________________________________________________________
conv2d_295 (Conv2D)             (None, 14, 14, 256)  172032      activation_263[0][0]             
__________________________________________________________________________________________________
batch_normalization_261 (BatchN (None, 14, 14, 192)  576         conv2d_292[0][0]                 
__________________________________________________________________________________________________
batch_normalization_264 (BatchN (None, 14, 14, 256)  768         conv2d_295[0][0]                 
__________________________________________________________________________________________________
activation_261 (Activation)     (None, 14, 14, 192)  0           batch_normalization_261[0][0]    
__________________________________________________________________________________________________
activation_264 (Activation)     (None, 14, 14, 256)  0           batch_normalization_264[0][0]    
__________________________________________________________________________________________________
block8_1_mixed (Concatenate)    (None, 14, 14, 448)  0           activation_261[0][0]             
                                                                 activation_264[0][0]             
__________________________________________________________________________________________________
block8_1_conv (Conv2D)          (None, 14, 14, 2080) 933920      block8_1_mixed[0][0]             
__________________________________________________________________________________________________
block8_1 (Lambda)               (None, 14, 14, 2080) 0           mixed_7a[0][0]                   
                                                                 block8_1_conv[0][0]              
__________________________________________________________________________________________________
block8_1_ac (Activation)        (None, 14, 14, 2080) 0           block8_1[0][0]                   
__________________________________________________________________________________________________
conv2d_297 (Conv2D)             (None, 14, 14, 192)  399360      block8_1_ac[0][0]                
__________________________________________________________________________________________________
batch_normalization_266 (BatchN (None, 14, 14, 192)  576         conv2d_297[0][0]                 
__________________________________________________________________________________________________
activation_266 (Activation)     (None, 14, 14, 192)  0           batch_normalization_266[0][0]    
__________________________________________________________________________________________________
conv2d_298 (Conv2D)             (None, 14, 14, 224)  129024      activation_266[0][0]             
__________________________________________________________________________________________________
batch_normalization_267 (BatchN (None, 14, 14, 224)  672         conv2d_298[0][0]                 
__________________________________________________________________________________________________
activation_267 (Activation)     (None, 14, 14, 224)  0           batch_normalization_267[0][0]    
__________________________________________________________________________________________________
conv2d_296 (Conv2D)             (None, 14, 14, 192)  399360      block8_1_ac[0][0]                
__________________________________________________________________________________________________
conv2d_299 (Conv2D)             (None, 14, 14, 256)  172032      activation_267[0][0]             
__________________________________________________________________________________________________
batch_normalization_265 (BatchN (None, 14, 14, 192)  576         conv2d_296[0][0]                 
__________________________________________________________________________________________________
batch_normalization_268 (BatchN (None, 14, 14, 256)  768         conv2d_299[0][0]                 
__________________________________________________________________________________________________
activation_265 (Activation)     (None, 14, 14, 192)  0           batch_normalization_265[0][0]    
__________________________________________________________________________________________________
activation_268 (Activation)     (None, 14, 14, 256)  0           batch_normalization_268[0][0]    
__________________________________________________________________________________________________
block8_2_mixed (Concatenate)    (None, 14, 14, 448)  0           activation_265[0][0]             
                                                                 activation_268[0][0]             
__________________________________________________________________________________________________
block8_2_conv (Conv2D)          (None, 14, 14, 2080) 933920      block8_2_mixed[0][0]             
__________________________________________________________________________________________________
block8_2 (Lambda)               (None, 14, 14, 2080) 0           block8_1_ac[0][0]                
                                                                 block8_2_conv[0][0]              
__________________________________________________________________________________________________
block8_2_ac (Activation)        (None, 14, 14, 2080) 0           block8_2[0][0]                   
__________________________________________________________________________________________________
conv2d_301 (Conv2D)             (None, 14, 14, 192)  399360      block8_2_ac[0][0]                
__________________________________________________________________________________________________
batch_normalization_270 (BatchN (None, 14, 14, 192)  576         conv2d_301[0][0]                 
__________________________________________________________________________________________________
activation_270 (Activation)     (None, 14, 14, 192)  0           batch_normalization_270[0][0]    
__________________________________________________________________________________________________
conv2d_302 (Conv2D)             (None, 14, 14, 224)  129024      activation_270[0][0]             
__________________________________________________________________________________________________
batch_normalization_271 (BatchN (None, 14, 14, 224)  672         conv2d_302[0][0]                 
__________________________________________________________________________________________________
activation_271 (Activation)     (None, 14, 14, 224)  0           batch_normalization_271[0][0]    
__________________________________________________________________________________________________
conv2d_300 (Conv2D)             (None, 14, 14, 192)  399360      block8_2_ac[0][0]                
__________________________________________________________________________________________________
conv2d_303 (Conv2D)             (None, 14, 14, 256)  172032      activation_271[0][0]             
__________________________________________________________________________________________________
batch_normalization_269 (BatchN (None, 14, 14, 192)  576         conv2d_300[0][0]                 
__________________________________________________________________________________________________
batch_normalization_272 (BatchN (None, 14, 14, 256)  768         conv2d_303[0][0]                 
__________________________________________________________________________________________________
activation_269 (Activation)     (None, 14, 14, 192)  0           batch_normalization_269[0][0]    
__________________________________________________________________________________________________
activation_272 (Activation)     (None, 14, 14, 256)  0           batch_normalization_272[0][0]    
__________________________________________________________________________________________________
block8_3_mixed (Concatenate)    (None, 14, 14, 448)  0           activation_269[0][0]             
                                                                 activation_272[0][0]             
__________________________________________________________________________________________________
block8_3_conv (Conv2D)          (None, 14, 14, 2080) 933920      block8_3_mixed[0][0]             
__________________________________________________________________________________________________
block8_3 (Lambda)               (None, 14, 14, 2080) 0           block8_2_ac[0][0]                
                                                                 block8_3_conv[0][0]              
__________________________________________________________________________________________________
block8_3_ac (Activation)        (None, 14, 14, 2080) 0           block8_3[0][0]                   
__________________________________________________________________________________________________
conv2d_305 (Conv2D)             (None, 14, 14, 192)  399360      block8_3_ac[0][0]                
__________________________________________________________________________________________________
batch_normalization_274 (BatchN (None, 14, 14, 192)  576         conv2d_305[0][0]                 
__________________________________________________________________________________________________
activation_274 (Activation)     (None, 14, 14, 192)  0           batch_normalization_274[0][0]    
__________________________________________________________________________________________________
conv2d_306 (Conv2D)             (None, 14, 14, 224)  129024      activation_274[0][0]             
__________________________________________________________________________________________________
batch_normalization_275 (BatchN (None, 14, 14, 224)  672         conv2d_306[0][0]                 
__________________________________________________________________________________________________
activation_275 (Activation)     (None, 14, 14, 224)  0           batch_normalization_275[0][0]    
__________________________________________________________________________________________________
conv2d_304 (Conv2D)             (None, 14, 14, 192)  399360      block8_3_ac[0][0]                
__________________________________________________________________________________________________
conv2d_307 (Conv2D)             (None, 14, 14, 256)  172032      activation_275[0][0]             
__________________________________________________________________________________________________
batch_normalization_273 (BatchN (None, 14, 14, 192)  576         conv2d_304[0][0]                 
__________________________________________________________________________________________________
batch_normalization_276 (BatchN (None, 14, 14, 256)  768         conv2d_307[0][0]                 
__________________________________________________________________________________________________
activation_273 (Activation)     (None, 14, 14, 192)  0           batch_normalization_273[0][0]    
__________________________________________________________________________________________________
activation_276 (Activation)     (None, 14, 14, 256)  0           batch_normalization_276[0][0]    
__________________________________________________________________________________________________
block8_4_mixed (Concatenate)    (None, 14, 14, 448)  0           activation_273[0][0]             
                                                                 activation_276[0][0]             
__________________________________________________________________________________________________
block8_4_conv (Conv2D)          (None, 14, 14, 2080) 933920      block8_4_mixed[0][0]             
__________________________________________________________________________________________________
block8_4 (Lambda)               (None, 14, 14, 2080) 0           block8_3_ac[0][0]                
                                                                 block8_4_conv[0][0]              
__________________________________________________________________________________________________
block8_4_ac (Activation)        (None, 14, 14, 2080) 0           block8_4[0][0]                   
__________________________________________________________________________________________________
conv2d_309 (Conv2D)             (None, 14, 14, 192)  399360      block8_4_ac[0][0]                
__________________________________________________________________________________________________
batch_normalization_278 (BatchN (None, 14, 14, 192)  576         conv2d_309[0][0]                 
__________________________________________________________________________________________________
activation_278 (Activation)     (None, 14, 14, 192)  0           batch_normalization_278[0][0]    
__________________________________________________________________________________________________
conv2d_310 (Conv2D)             (None, 14, 14, 224)  129024      activation_278[0][0]             
__________________________________________________________________________________________________
batch_normalization_279 (BatchN (None, 14, 14, 224)  672         conv2d_310[0][0]                 
__________________________________________________________________________________________________
activation_279 (Activation)     (None, 14, 14, 224)  0           batch_normalization_279[0][0]    
__________________________________________________________________________________________________
conv2d_308 (Conv2D)             (None, 14, 14, 192)  399360      block8_4_ac[0][0]                
__________________________________________________________________________________________________
conv2d_311 (Conv2D)             (None, 14, 14, 256)  172032      activation_279[0][0]             
__________________________________________________________________________________________________
batch_normalization_277 (BatchN (None, 14, 14, 192)  576         conv2d_308[0][0]                 
__________________________________________________________________________________________________
batch_normalization_280 (BatchN (None, 14, 14, 256)  768         conv2d_311[0][0]                 
__________________________________________________________________________________________________
activation_277 (Activation)     (None, 14, 14, 192)  0           batch_normalization_277[0][0]    
__________________________________________________________________________________________________
activation_280 (Activation)     (None, 14, 14, 256)  0           batch_normalization_280[0][0]    
__________________________________________________________________________________________________
block8_5_mixed (Concatenate)    (None, 14, 14, 448)  0           activation_277[0][0]             
                                                                 activation_280[0][0]             
__________________________________________________________________________________________________
block8_5_conv (Conv2D)          (None, 14, 14, 2080) 933920      block8_5_mixed[0][0]             
__________________________________________________________________________________________________
block8_5 (Lambda)               (None, 14, 14, 2080) 0           block8_4_ac[0][0]                
                                                                 block8_5_conv[0][0]              
__________________________________________________________________________________________________
block8_5_ac (Activation)        (None, 14, 14, 2080) 0           block8_5[0][0]                   
__________________________________________________________________________________________________
conv2d_313 (Conv2D)             (None, 14, 14, 192)  399360      block8_5_ac[0][0]                
__________________________________________________________________________________________________
batch_normalization_282 (BatchN (None, 14, 14, 192)  576         conv2d_313[0][0]                 
__________________________________________________________________________________________________
activation_282 (Activation)     (None, 14, 14, 192)  0           batch_normalization_282[0][0]    
__________________________________________________________________________________________________
conv2d_314 (Conv2D)             (None, 14, 14, 224)  129024      activation_282[0][0]             
__________________________________________________________________________________________________
batch_normalization_283 (BatchN (None, 14, 14, 224)  672         conv2d_314[0][0]                 
__________________________________________________________________________________________________
activation_283 (Activation)     (None, 14, 14, 224)  0           batch_normalization_283[0][0]    
__________________________________________________________________________________________________
conv2d_312 (Conv2D)             (None, 14, 14, 192)  399360      block8_5_ac[0][0]                
__________________________________________________________________________________________________
conv2d_315 (Conv2D)             (None, 14, 14, 256)  172032      activation_283[0][0]             
__________________________________________________________________________________________________
batch_normalization_281 (BatchN (None, 14, 14, 192)  576         conv2d_312[0][0]                 
__________________________________________________________________________________________________
batch_normalization_284 (BatchN (None, 14, 14, 256)  768         conv2d_315[0][0]                 
__________________________________________________________________________________________________
activation_281 (Activation)     (None, 14, 14, 192)  0           batch_normalization_281[0][0]    
__________________________________________________________________________________________________
activation_284 (Activation)     (None, 14, 14, 256)  0           batch_normalization_284[0][0]    
__________________________________________________________________________________________________
block8_6_mixed (Concatenate)    (None, 14, 14, 448)  0           activation_281[0][0]             
                                                                 activation_284[0][0]             
__________________________________________________________________________________________________
block8_6_conv (Conv2D)          (None, 14, 14, 2080) 933920      block8_6_mixed[0][0]             
__________________________________________________________________________________________________
block8_6 (Lambda)               (None, 14, 14, 2080) 0           block8_5_ac[0][0]                
                                                                 block8_6_conv[0][0]              
__________________________________________________________________________________________________
block8_6_ac (Activation)        (None, 14, 14, 2080) 0           block8_6[0][0]                   
__________________________________________________________________________________________________
conv2d_317 (Conv2D)             (None, 14, 14, 192)  399360      block8_6_ac[0][0]                
__________________________________________________________________________________________________
batch_normalization_286 (BatchN (None, 14, 14, 192)  576         conv2d_317[0][0]                 
__________________________________________________________________________________________________
activation_286 (Activation)     (None, 14, 14, 192)  0           batch_normalization_286[0][0]    
__________________________________________________________________________________________________
conv2d_318 (Conv2D)             (None, 14, 14, 224)  129024      activation_286[0][0]             
__________________________________________________________________________________________________
batch_normalization_287 (BatchN (None, 14, 14, 224)  672         conv2d_318[0][0]                 
__________________________________________________________________________________________________
activation_287 (Activation)     (None, 14, 14, 224)  0           batch_normalization_287[0][0]    
__________________________________________________________________________________________________
conv2d_316 (Conv2D)             (None, 14, 14, 192)  399360      block8_6_ac[0][0]                
__________________________________________________________________________________________________
conv2d_319 (Conv2D)             (None, 14, 14, 256)  172032      activation_287[0][0]             
__________________________________________________________________________________________________
batch_normalization_285 (BatchN (None, 14, 14, 192)  576         conv2d_316[0][0]                 
__________________________________________________________________________________________________
batch_normalization_288 (BatchN (None, 14, 14, 256)  768         conv2d_319[0][0]                 
__________________________________________________________________________________________________
activation_285 (Activation)     (None, 14, 14, 192)  0           batch_normalization_285[0][0]    
__________________________________________________________________________________________________
activation_288 (Activation)     (None, 14, 14, 256)  0           batch_normalization_288[0][0]    
__________________________________________________________________________________________________
block8_7_mixed (Concatenate)    (None, 14, 14, 448)  0           activation_285[0][0]             
                                                                 activation_288[0][0]             
__________________________________________________________________________________________________
block8_7_conv (Conv2D)          (None, 14, 14, 2080) 933920      block8_7_mixed[0][0]             
__________________________________________________________________________________________________
block8_7 (Lambda)               (None, 14, 14, 2080) 0           block8_6_ac[0][0]                
                                                                 block8_7_conv[0][0]              
__________________________________________________________________________________________________
block8_7_ac (Activation)        (None, 14, 14, 2080) 0           block8_7[0][0]                   
__________________________________________________________________________________________________
conv2d_321 (Conv2D)             (None, 14, 14, 192)  399360      block8_7_ac[0][0]                
__________________________________________________________________________________________________
batch_normalization_290 (BatchN (None, 14, 14, 192)  576         conv2d_321[0][0]                 
__________________________________________________________________________________________________
activation_290 (Activation)     (None, 14, 14, 192)  0           batch_normalization_290[0][0]    
__________________________________________________________________________________________________
conv2d_322 (Conv2D)             (None, 14, 14, 224)  129024      activation_290[0][0]             
__________________________________________________________________________________________________
batch_normalization_291 (BatchN (None, 14, 14, 224)  672         conv2d_322[0][0]                 
__________________________________________________________________________________________________
activation_291 (Activation)     (None, 14, 14, 224)  0           batch_normalization_291[0][0]    
__________________________________________________________________________________________________
conv2d_320 (Conv2D)             (None, 14, 14, 192)  399360      block8_7_ac[0][0]                
__________________________________________________________________________________________________
conv2d_323 (Conv2D)             (None, 14, 14, 256)  172032      activation_291[0][0]             
__________________________________________________________________________________________________
batch_normalization_289 (BatchN (None, 14, 14, 192)  576         conv2d_320[0][0]                 
__________________________________________________________________________________________________
batch_normalization_292 (BatchN (None, 14, 14, 256)  768         conv2d_323[0][0]                 
__________________________________________________________________________________________________
activation_289 (Activation)     (None, 14, 14, 192)  0           batch_normalization_289[0][0]    
__________________________________________________________________________________________________
activation_292 (Activation)     (None, 14, 14, 256)  0           batch_normalization_292[0][0]    
__________________________________________________________________________________________________
block8_8_mixed (Concatenate)    (None, 14, 14, 448)  0           activation_289[0][0]             
                                                                 activation_292[0][0]             
__________________________________________________________________________________________________
block8_8_conv (Conv2D)          (None, 14, 14, 2080) 933920      block8_8_mixed[0][0]             
__________________________________________________________________________________________________
block8_8 (Lambda)               (None, 14, 14, 2080) 0           block8_7_ac[0][0]                
                                                                 block8_8_conv[0][0]              
__________________________________________________________________________________________________
block8_8_ac (Activation)        (None, 14, 14, 2080) 0           block8_8[0][0]                   
__________________________________________________________________________________________________
conv2d_325 (Conv2D)             (None, 14, 14, 192)  399360      block8_8_ac[0][0]                
__________________________________________________________________________________________________
batch_normalization_294 (BatchN (None, 14, 14, 192)  576         conv2d_325[0][0]                 
__________________________________________________________________________________________________
activation_294 (Activation)     (None, 14, 14, 192)  0           batch_normalization_294[0][0]    
__________________________________________________________________________________________________
conv2d_326 (Conv2D)             (None, 14, 14, 224)  129024      activation_294[0][0]             
__________________________________________________________________________________________________
batch_normalization_295 (BatchN (None, 14, 14, 224)  672         conv2d_326[0][0]                 
__________________________________________________________________________________________________
activation_295 (Activation)     (None, 14, 14, 224)  0           batch_normalization_295[0][0]    
__________________________________________________________________________________________________
conv2d_324 (Conv2D)             (None, 14, 14, 192)  399360      block8_8_ac[0][0]                
__________________________________________________________________________________________________
conv2d_327 (Conv2D)             (None, 14, 14, 256)  172032      activation_295[0][0]             
__________________________________________________________________________________________________
batch_normalization_293 (BatchN (None, 14, 14, 192)  576         conv2d_324[0][0]                 
__________________________________________________________________________________________________
batch_normalization_296 (BatchN (None, 14, 14, 256)  768         conv2d_327[0][0]                 
__________________________________________________________________________________________________
activation_293 (Activation)     (None, 14, 14, 192)  0           batch_normalization_293[0][0]    
__________________________________________________________________________________________________
activation_296 (Activation)     (None, 14, 14, 256)  0           batch_normalization_296[0][0]    
__________________________________________________________________________________________________
block8_9_mixed (Concatenate)    (None, 14, 14, 448)  0           activation_293[0][0]             
                                                                 activation_296[0][0]             
__________________________________________________________________________________________________
block8_9_conv (Conv2D)          (None, 14, 14, 2080) 933920      block8_9_mixed[0][0]             
__________________________________________________________________________________________________
block8_9 (Lambda)               (None, 14, 14, 2080) 0           block8_8_ac[0][0]                
                                                                 block8_9_conv[0][0]              
__________________________________________________________________________________________________
block8_9_ac (Activation)        (None, 14, 14, 2080) 0           block8_9[0][0]                   
__________________________________________________________________________________________________
conv2d_329 (Conv2D)             (None, 14, 14, 192)  399360      block8_9_ac[0][0]                
__________________________________________________________________________________________________
batch_normalization_298 (BatchN (None, 14, 14, 192)  576         conv2d_329[0][0]                 
__________________________________________________________________________________________________
activation_298 (Activation)     (None, 14, 14, 192)  0           batch_normalization_298[0][0]    
__________________________________________________________________________________________________
conv2d_330 (Conv2D)             (None, 14, 14, 224)  129024      activation_298[0][0]             
__________________________________________________________________________________________________
batch_normalization_299 (BatchN (None, 14, 14, 224)  672         conv2d_330[0][0]                 
__________________________________________________________________________________________________
activation_299 (Activation)     (None, 14, 14, 224)  0           batch_normalization_299[0][0]    
__________________________________________________________________________________________________
conv2d_328 (Conv2D)             (None, 14, 14, 192)  399360      block8_9_ac[0][0]                
__________________________________________________________________________________________________
conv2d_331 (Conv2D)             (None, 14, 14, 256)  172032      activation_299[0][0]             
__________________________________________________________________________________________________
batch_normalization_297 (BatchN (None, 14, 14, 192)  576         conv2d_328[0][0]                 
__________________________________________________________________________________________________
batch_normalization_300 (BatchN (None, 14, 14, 256)  768         conv2d_331[0][0]                 
__________________________________________________________________________________________________
activation_297 (Activation)     (None, 14, 14, 192)  0           batch_normalization_297[0][0]    
__________________________________________________________________________________________________
activation_300 (Activation)     (None, 14, 14, 256)  0           batch_normalization_300[0][0]    
__________________________________________________________________________________________________
block8_10_mixed (Concatenate)   (None, 14, 14, 448)  0           activation_297[0][0]             
                                                                 activation_300[0][0]             
__________________________________________________________________________________________________
block8_10_conv (Conv2D)         (None, 14, 14, 2080) 933920      block8_10_mixed[0][0]            
__________________________________________________________________________________________________
block8_10 (Lambda)              (None, 14, 14, 2080) 0           block8_9_ac[0][0]                
                                                                 block8_10_conv[0][0]             
__________________________________________________________________________________________________
conv_7b (Conv2D)                (None, 14, 14, 1536) 3194880     block8_10[0][0]                  
__________________________________________________________________________________________________
conv_7b_bn (BatchNormalization) (None, 14, 14, 1536) 4608        conv_7b[0][0]                    
__________________________________________________________________________________________________
conv_7b_ac (Activation)         (None, 14, 14, 1536) 0           conv_7b_bn[0][0]                 
__________________________________________________________________________________________________
global_average_pooling2d_3 (Glo (None, 1536)         0           conv_7b_ac[0][0]                 
__________________________________________________________________________________________________
dense_12 (Dense)                (None, 516)          793092      global_average_pooling2d_3[0][0] 
__________________________________________________________________________________________________
dropout_6 (Dropout)             (None, 516)          0           dense_12[0][0]                   
__________________________________________________________________________________________________
dense_13 (Dense)                (None, 256)          132352      dropout_6[0][0]                  
__________________________________________________________________________________________________
dropout_7 (Dropout)             (None, 256)          0           dense_13[0][0]                   
__________________________________________________________________________________________________
dense_14 (Dense)                (None, 64)           16448       dropout_7[0][0]                  
__________________________________________________________________________________________________
dense_15 (Dense)                (None, 3)            195         dense_14[0][0]                   
==================================================================================================
Total params: 55,278,823
Trainable params: 13,383,143
Non-trainable params: 41,895,680
__________________________________________________________________________________________________
None
In [25]:
# Define modifier to replace the sigmoid function of the last layer to a linear function
def model_modifier(m):
    m.layers[-1].activation = tf.keras.activations.linear

# Define losses functions. 0 is the index for a normal MRI
loss_normal = lambda output: K.mean(output[:, 0])

# Define losses functions. 1 is the index for a diffuse malformation of cortical development MRI
loss_diffuseMCD = lambda output: K.mean(output[:, 1])

# Define losses functions. 2 is the index for a PVNH MRI
loss_PVNH = lambda output: K.mean(output[:, 2])
    
# Create Gradcam object
gradcam = Gradcam(model, model_modifier)

# Create Saliency object
saliency = Saliency(model, model_modifier)

# Iterate through the MRIs in test set

# Set background to white color
plt.rcParams['axes.facecolor']='white'
plt.rcParams['figure.facecolor']='white'
plt.rcParams['figure.edgecolor']='white'


print('\n \n' + '\033[1m' + 'EACH ORIGINAL MRI IS ANALYZED WITH TWO METHODS: CLASS ACTIVATION MAP (UPPER ROW) AND SALIENCY MAP (LOWER ROW)' + '\033[0m' + '\n')
print('\033[1m' + 'EACH MAP IS SUPERIMPOSED ON THE ORIGINAL MRI WITH A TRANSPARENCY THAT IS INVERSELY PROPORTIONAL TO THE ESTIMATED PROBABILITY OF THE MRI BELONGING TO THAT CATEGORY (NORMAL MRI, DIFFUSE CORTICAL MALFORMATION, OR PERIVENTRICULAR NODULAR HETEROTOPIA) \n \nHIGHER ESTIMATED PROBABILITIES PRODUCE CLEARLY SEEN MAPS OVERLAID ON THE ORIGINAL MRI AND LOWER ESTIMATED PROBABILITIES PRODUCE VERY TRANSPARENT OR NOT APPRECIABLE MAPS OVERLAID ON THE ORIGINAL MRI' + '\033[0m'+ '\n')


# print images 700 to 766
for i in range(700, 765):
    
    # Print spaces to separate from the next image
    print('\n \n \n \n \n \n')
  
    # Print real classification of the image
    if y_true[i]==0:
        real_classification='Normal MRI'
    elif y_true[i]==1:
        real_classification='Diffuse MCD'
    else:
        real_classification='PVNH'
        
    print('\033[1m' + 'REAL CLASSIFICATION OF THE IMAGE: {}'.format(real_classification) + '\033[0m')
   
    # Print model classification and model probability of MCD
    if y_predInceptionResNetV2[i]==0:
        predicted_classification='Normal MRI'
    elif y_predInceptionResNetV2[i]==1:
        predicted_classification='Diffuse MCD'
    else:
        predicted_classification='PVNH'   
    
    print('\033[1m' + 'MODEL CLASSIFICATION OF THE IMAGE: {}'.format(predicted_classification)  + '\033[0m \n') 
    print('\033[1m' + '   Prob. Normal MRI: {:.4f}    '.format(testInceptionResNetV2[i][0]) + 'Prob. Diffuse MCD: {:.4f}     '.format(testInceptionResNetV2[i][1]), 'Prob. PVNH: {:.4f}'.format(testInceptionResNetV2[i][2]) + '\033[0m')
  
    
    # Arrays to plot
    original_image=shuffled_test_X[i]
    list_heatmaps=[
        # GradCam heatmap for normal MRI
        normalize(gradcam(loss_normal, shuffled_test_X[i])),
        # GradCam heatmap for diffuse MCD
        normalize(gradcam(loss_diffuseMCD, shuffled_test_X[i])),
        # GradCam heatmap for PVNH
        normalize(gradcam(loss_PVNH, shuffled_test_X[i])),
        # Saliency heatmap for normal MRI
        normalize(saliency(loss_normal, seed_input=np.expand_dims(shuffled_test_X[i], axis=0), smooth_noise=0.2)),
        # Saliency heatmap for diffuse MCD
        normalize(saliency(loss_diffuseMCD, seed_input=np.expand_dims(shuffled_test_X[i], axis=0), smooth_noise=0.2)),
        # Saliency heatmap for PVNH
        normalize(saliency(loss_PVNH, seed_input=np.expand_dims(shuffled_test_X[i], axis=0), smooth_noise=0.2))
    ]
    
    # Define figure
    f=plt.figure(figsize=(20, 8))

    # Define the image grid
    grid = ImageGrid(f, 111,
                nrows_ncols=(2, 3),
                axes_pad=0.05,
                share_all=True,
                cbar_location="right",
                cbar_mode=None,
                cbar_size="2%",
                cbar_pad=0.15)

    
    # Iterate over the graphs
    for j, axis in enumerate(grid):
        # Plot original 
        im=axis.imshow(original_image)
        im=axis.imshow(list_heatmaps[j][0], cmap='jet', alpha=0.5*testInceptionResNetV2[i][j%3])
        im=axis.set_xticks([])
        im=axis.set_yticks([])
    
    # Create scalarmappable for obtaining the colorbar from 0 to 1
    sm = plt.cm.ScalarMappable(cmap='jet', norm=plt.Normalize(vmin=0, vmax=1))
    plt.colorbar(sm)
    plt.show()
 
EACH ORIGINAL MRI IS ANALYZED WITH TWO METHODS: CLASS ACTIVATION MAP (UPPER ROW) AND SALIENCY MAP (LOWER ROW)

EACH MAP IS SUPERIMPOSED ON THE ORIGINAL MRI WITH A TRANSPARENCY THAT IS INVERSELY PROPORTIONAL TO THE ESTIMATED PROBABILITY OF THE MRI BELONGING TO THAT CATEGORY (NORMAL MRI, DIFFUSE CORTICAL MALFORMATION, OR PERIVENTRICULAR NODULAR HETEROTOPIA) 
 
HIGHER ESTIMATED PROBABILITIES PRODUCE CLEARLY SEEN MAPS OVERLAID ON THE ORIGINAL MRI AND LOWER ESTIMATED PROBABILITIES PRODUCE VERY TRANSPARENT OR NOT APPRECIABLE MAPS OVERLAID ON THE ORIGINAL MRI


 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 1.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 0.9993    Prob. Diffuse MCD: 0.0003      Prob. PVNH: 0.0004
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0042    Prob. Diffuse MCD: 0.0059      Prob. PVNH: 0.9899
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 0.8080    Prob. Diffuse MCD: 0.0076      Prob. PVNH: 0.1844
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 0.6936    Prob. Diffuse MCD: 0.0317      Prob. PVNH: 0.2747
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.1176    Prob. Diffuse MCD: 0.0240      Prob. PVNH: 0.8584
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 0.7982    Prob. Diffuse MCD: 0.1482      Prob. PVNH: 0.0537
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0005    Prob. Diffuse MCD: 0.9985      Prob. PVNH: 0.0010
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0005    Prob. Diffuse MCD: 0.0051      Prob. PVNH: 0.9944
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0002    Prob. Diffuse MCD: 0.0012      Prob. PVNH: 0.9986
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.9999      Prob. PVNH: 0.0001
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 1.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 1.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.3587    Prob. Diffuse MCD: 0.0001      Prob. PVNH: 0.6412
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 1.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 1.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 0.9974    Prob. Diffuse MCD: 0.0020      Prob. PVNH: 0.0005
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 0.9990    Prob. Diffuse MCD: 0.0001      Prob. PVNH: 0.0009
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 1.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0001    Prob. Diffuse MCD: 0.0003      Prob. PVNH: 0.9996
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 0.9999    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0004    Prob. Diffuse MCD: 0.0002      Prob. PVNH: 0.9994
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 0.8501    Prob. Diffuse MCD: 0.0090      Prob. PVNH: 0.1409
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 1.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 1.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.2524    Prob. Diffuse MCD: 0.6769      Prob. PVNH: 0.0708
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0870    Prob. Diffuse MCD: 0.8178      Prob. PVNH: 0.0952
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0005    Prob. Diffuse MCD: 0.0015      Prob. PVNH: 0.9979
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 0.9382    Prob. Diffuse MCD: 0.0069      Prob. PVNH: 0.0549
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 0.9272    Prob. Diffuse MCD: 0.0081      Prob. PVNH: 0.0647
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: PVNH
MODEL CLASSIFICATION OF THE IMAGE: PVNH 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 1.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0909    Prob. Diffuse MCD: 0.8759      Prob. PVNH: 0.0332
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Normal MRI
MODEL CLASSIFICATION OF THE IMAGE: Normal MRI 

   Prob. Normal MRI: 1.0000    Prob. Diffuse MCD: 0.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 1.0000      Prob. PVNH: 0.0000
 
 
 
 
 

REAL CLASSIFICATION OF THE IMAGE: Diffuse MCD
MODEL CLASSIFICATION OF THE IMAGE: Diffuse MCD 

   Prob. Normal MRI: 0.0000    Prob. Diffuse MCD: 1.0000      Prob. PVNH: 0.0000

SCROLL UP TO SEE THE GradCAM AND SALIENCY MAPS

Each original image is analyzed with two methods: Gradient-weighted class activation maps (upper row) and saliency maps (lower row).

Each map is superimposed on the original MRI with a transparency that is inversely proportional to the estimated probability of the MRI belonging to that category (normal MRI, diffuse cortical malformation, or periventricular nodular heterotopia). Higher estimated probabilities produce clearly seen maps overlaid on the original MRI and lower estimated probabilities produce very transparent or not appreciable maps overlaid on the original MRI.